POSITION DETERMINATION BASED ON PROPAGATION DELAY DIFFERENCES OF MULTIPLE SIGNALS RECEIVED AT MULTIPLE SENSORS

Abstract

Methods and systems to determine at multi-dimensional coordinates of an object based on propagation delay differences of multiple signals received from the object by each of a plurality of sensors. The signals may include optical signals in a human visible spectrum, which may be amplitude modulated with corresponding frequency tones. An envelope may be detected with respect to each of the sensors, and signals within each envelope may be separated. A phase difference of arrival may be determined for each of the signals, based on a difference in propagation delay times of the signal with respect to multiple sensors. The phase differences of arrival may be converted to corresponding distance differences between a corresponding transmitter and the corresponding sensors. A linear distance and a perpendicular offset distance may be determined from a combination the distance differences, a distance between the corresponding transmitters, and a distance between the corresponding sensors.

Description

BACKGROUND

Systems have been developed to determine a two-dimensional position of an automobile based on satellite-based global positioning system (GPS) information.

Systems have been developed to determine a position of an object relative to known fixed positions of three or more transmitters, based on phase differences of signals received from the three or more transmitters.

BRIEF DESCRIPTION OF THE DRAWINGS/FIGURES

FIG. 1 is a block diagram of a system to determine multi-dimensional coordinates of an object based on one way communication from the object.

FIG. 2 is a block diagram of the object including tone generators.

FIG. 3 is a block diagram of the object including tone generators and radio frequency (RF) modulators.

FIG. 4 is a block diagram of the object including tone generators and light modulators.

FIG. 5 is a graphic depiction of a first signal received from the object at first and second sensors, with corresponding propagation time delays τ₁ and τ₂.

FIG. 6 is a graphic depiction of a second signal received from the object at the first and second sensors, with corresponding propagation time delays τ₃ and τ₄.

FIG. 7 is a graphic depiction of distances L₁ and L₂, between a first transmitter and each of first and second sensors, and distances L₃ and L₄ between a second transmitter and each of the first and second sensors.

FIG. 8 is a block diagram of a system to process the first and second signals received at each of the first and second sensors.

FIG. 9 is a graphic depiction of geometries illustrated in FIGS. 1 and 7, in an x-y plane.

FIG. 10 is a graphic depiction of the geometries of FIG. 9, where L₁=L₂.

FIG. 11 is a graphic depiction of the geometries of FIG. 9, where L₃=L₄.

FIG. 12 is a graphic depiction of a triangle of FIG. 11, having a hypotenuse of L₁.

FIG. 13 is a graphic depiction of a triangle of FIG. 11, having a hypotenuse of L₂.

FIG. 14 is a graphic depiction of coordinates of the object in an x-y plane.

FIG. 15 is a process flowchart of a method of determining multi-dimensional coordinates of an object based on propagation delay differences of multiple signals received at multiple sensors.

FIG. 16 is a block diagram of a computer system configured to determine multi-dimensional coordinates of an object based on propagation delay differences of multiple signals received at multiple sensors.

In the drawings, the leftmost digit(s) of a reference number identifies the drawing in which the reference number first appears.

DETAILED DESCRIPTION

Disclosed herein are methods and systems to determine multi-dimensional coordinates of an object based on propagation delay differences of multiple signals received from the object by each of a plurality of sensors.

FIG. 1 is a block diagram of a system 102 to determine multi-dimensional coordinates of an object 104 based on one way communication from the object.

Object 104 may represent a movable object, such as an automobile.

System 102 may be implemented within a movable object, such as an automobile. Alternatively, system 102 may be implemented as a stationary system.

Object 104 includes a plurality of signal radiator systems, illustrated here as first and second signal radiator systems 110 and 112 to generate and radiate corresponding signals S₁ and S₂, having corresponding baseband ranging waveforms or frequency tones, referred to generally as tones, ω₁ and ω₂. Tones ω₁ and ω₂ may include continuous wave (CW) radio frequency (RF) tones. Signals S₁ and S₂ may each include one or more of a radio frequency (RF) tone, an RF carrier modulated with a tone, and a light wave carrier modulated with a tone, such as described below with respect to FIGS. 2-4, respectively.

FIG. 2 is a block diagram of object 104 wherein radiators 110 and 112 include tone generators 202 and 204 to generate corresponding baseband ranging waveforms or frequency tones, referred to generally as tones, ω₁ and ω₂, and antennas 206 and 208 to radiate corresponding tones ω₁ and ω₂ as signals S₁ and S₂.

FIG. 3 is a block diagram of object 104, including a local oscillator 302 to generate a local oscillator frequency (LO) 304, wherein radiators 110 and 112 include tone generators 306 and 308 to generate tones ω₁ and ω₂, modulators 310 and 312 to modulate LO 304 with tones ω₁ and ω₂, and antennas 314 and 316 to radiate corresponding modulated tones ω₁ and ω₂ as signals S₁ and S₂. Modulators 310 and 312 may include amplitude modulators, such as described below.

FIG. 4 is a block diagram of object 104, wherein radiators 110 and 112 include tone generators 402 and 404 to generate tones ω₁ and ω₂, and light emitters 406 and 408 to modulate and emit light with tones ω₁ and ω₂ as signals S₁ and S₂. Light emitters 406 may include light emitting diodes (LEDs), and may include amplitude modulators, such as described below.

System 102 includes a plurality of sensors, illustrated here as first and second sensors 114 and 116, which may include optical sensors and/or RF receivers, each to receive both of signals S₁ and S₂.

System 102 further includes a relative position computation system 118 to determine a multi-dimensional position of object 104. In the example of FIG. 1, system 118 is configured to determine a linear distance X_A between system 102 and object 104, and a perpendicular offset distance Y_B between system 102 and object 104.

Perpendicular offset distance Y_B may correspond to a lateral offset distance or a vertical offset distance.

The combination of linear distance X_A and perpendicular offset distance Y_B provides a two dimensional or planar position of object 104 relative to system 102.

Object 104 may include one or more additional radiator systems, and/or system 102 may include one or more additional sensors, and system 118 may be configured to determine a position of object 104 in three or more dimensions.

System 118 may be configured to determine a position of object 104 based a combination of distance D between radiator systems 110 and 112, a distance X_A between sensors 114 and 116, a propagation delay difference of signal S₁ as received at sensors 114 and 116, and a propagation delay difference of signal S₂ as received at sensors 114 and 116. Propagation delay differences are described below with respect to FIGS. 5 and 6.

FIG. 5 is a graphic depiction of signal S₁ arriving at sensors 114 and 116, wherein signal S₁ arrives at sensor 114 with a propagation time delay τ₁, and at sensor 116 with a propagation time delay τ₂. Depending upon an angle of incidence of signal S₁ relative to a plane of sensors 114 and 116, τ₁ may be greater than, equal to, or less than τ₂.

FIG. 6 is a graphic depiction of signal S₂ arriving at sensors 114 and 116, wherein signal S₂ arrives at sensor 114 with a propagation time delay τ₃, and at sensor 116 with a propagation time delay τ₄. Depending upon an angle of incidence of signal S₂ relative to the plane of sensors 114 and 116, τ₃ may be greater than, equal to, or less than τ₄.

System 118 may be configured to determine linear distance X_A and perpendicular offset distance Y_B, in FIG. 1, from a combination of a difference between τ₁ and τ₂, a difference between τ₃ and τ₄, and distances D and Y_A.

For example, signals S₁ and S₂ may be modulated with corresponding frequency tones ω₁ and ω₂, such as illustrated in FIG. 1, and system 118 may be configured to:

• • determine a phase difference of arrival φ_Δ12 (FIG. 5) from a combination of ω₁ and a difference between τ₁ and τ₂;
  • determine a phase difference of arrival φ_Δ34 (FIG. 6) from a combination of ω₂ and a difference between τ₃ and τ₄;
  • convert phase difference of arrival φ_Δ12 to a distance difference Δ_L12, corresponding to difference between a distance from emitter 110 to each of sensors 114 and 116;
  • convert phase difference of arrival φ_Δ34 to a distance difference Δ_L34, corresponding to difference between a distance from emitter 112 to each of sensors 114 and 116; and
  • determine linear distance X_A and perpendicular offset distance Y_B from a combination of distance differences Δ_L12 and Δ_L34, and distances D and Y_A.

FIG. 7 is a graphic depiction of distances L₁ and L₂, between radiator system 110 and corresponding ones of sensors 114 and 116, and distances L₃ and L₄ between radiator system 112 and corresponding ones of sensors 114 and 116. Distance difference Δ_L12 corresponds to a difference between L₁ and L₂. Distance difference Δ_L34 corresponds to a difference between L₃ and L₃.

Example methods and systems to determine a position of object 104 are provided below wherein system 102 and object 104 are implemented with respect to automobiles, such as cars. The example methods and systems are not, however, limited to cars or automobiles.

Radiator systems 110 and 112 may be implemented proximate to, or integrated within headlights of car 104, and may include visible light emitters, such as light emitting diodes (LEDs).

Sensors 114 and 116 may be implemented proximate to, or integrated within tail lights of car 102, and may include photo-detectors. Alternatively, or additionally, one or more of sensors 114 and 116 may include an imaging system, which may include one or more of a charge-coupled device (CCD) and a lens system, to provide additional information to system 118, such as directionality information.

System 118 may be configured to determine a position of car 104 based on signals S₁ and S₂, without communicating to car 104, referred to herein as one-way positioning.

Car 104 may be configured to transmit an indication of distance D to car 102.

Where radiator systems 110 and 112 include visible light emitters, system 102 is referred to herein as a one-way positioning visible light communication (VLC) positioning system.

Signal radiator systems 110 and 112 may be configured to modulate headlights 110 and 112 with corresponding frequency tones ω₁ and ω₂, which may include amplitude modulation (AM). The amplitude modulation may include on-off keying, such as in accordance with a square wave.

Signal radiator systems 110 and 112 may be configured to generate optical carrier signals having a frequency bandwidth in a visible spectrum, which may include a frequency of approximately 500 tera Hertz (THz). The optical carrier signals may have a relatively large bandwidth, such as, for example, approximately several hundred mega HZ (MHz).

On-off keying amplitude modulation of a relatively wideband signal in a visible spectrum may permit signal radiator systems 110 and 112 to be implemented with relatively inexpensive components.

System 118 may be configured to determine a relative position of car 104 based on sub-carrier tone modulation of LED-based light sources 110 and 112.

System 118 may be configured to filter around a demodulated envelope of a carrier signal to extract corresponding RF tones ω₁ and ω₂.

Where signals S₁ and S₂ are amplitude modulated, signals received at each sensor 114 and 116, due to either of signals S₁ and S₂ may be represented as:

s _ik(t)=A_j(1+m·cos(ω_k(t+τ_j)+θ_k))cos(ω_C(t+τ_j)+θ_C)  (Eq. 1)

where:

• • s_ik(t) is the signal at the i^th sensor due to the modulation at the k^th headlight;
  • m is a modulation index (0<m≦1);
  • A_j is an attenuation of a j^th propagation path with propagation time delay τ_j; and
  • ω_k is the tone frequency with a starting phase of θ_k.

FIG. 8 is a block diagram of system 118, including a first path 802 to process signals received at sensor 114, and a second path 804 to process signals received at sensor 116. Alternatively, one or more portions of first and second paths may be combined in a common path.

Path 802 is described below. Path 804 may be implemented similar to path 804. Path 802 may include a non-coherent envelope detector 806 to detect envelopes of signals received at sensor 114.

An envelope of a signal received at either of sensors 114 and 116, due to either of signals S₁ and S₂, may be represented as:

s _ik(t)=A_j·m·cos(ω_k(t+τ_j)+θ_k)  (Eq. 2)

Equation 2 may be represented using upper sideband complex sinusoids, such as with digital signal processing, as:

$\begin{array}{cc}{s}_{\mathrm{ik}}\left(t\right)=\frac{A_j}{2}·m·{}^{j\left\{{\omega }_k\left(t+{\tau }_j\right)+{\theta }_k\right\}}& \left(\mathrm{Eq}.3\right)\end{array}$

A complex signal at each of taillights 114 and 116, due to signals S₁ and S₂, may be represented as:

$\begin{array}{cc}{s}_1\left(t\right)=\frac{A_1}{2}·m·{}^{j\left\{{\omega }_1\left(t+{\tau }_1\right)+{\theta }_1\right\}}+\frac{A_3}{2}·m·{}^{j\left\{{\omega }_2\left(t+{\tau }_3\right)+{\theta }_2\right\}}& \left(\mathrm{Eq}.4\right)\\ s_2\left(t\right)=\frac{A_2}{2}·m·{}^{j\left\{{\omega }_1\left(t+{\tau }_2\right)+{\theta }_1\right\}}+\frac{A_4}{2}·m·{}^{j\left\{{\omega }_2\left(t+{\tau }_4\right)+{\theta }_2\right\}}& \left(\mathrm{Eq}.5\right)\end{array}$

Path 802 may include a frequency converter 808 and a low pass filter (LPF) 810, such as described further below.

Path 802 may include a tone separator 812 to separate tones of signals S₁ and S₂ from envelopes detected by envelope detector 806. Tone separator 812 may include a band pass filter, which may include a Fast Fourier Transform (FFT) module, which may be implemented in a digital signal processor (DSP). The FFT module may include multiple FFT modules configured to overlap one another in time to provide a sampled, filtered sinusoid. Resultant amplitude and frequency bins may be examined to identify received tones.

Tones of signals S₁ and S₂, received at either of sensors 114 and 116, may be represented as:

$\begin{array}{cc}{s}_1^{{\omega }_1}\left(t\right)=\frac{A_1}{2}·m·{}^{j\left\{{\omega }_1\left(t+{\tau }_1\right)+{\theta }_1\right\}}& \left(\mathrm{Eq}.6\right)\\ s_1^{{\omega }_2}\left(t\right)=\frac{A_3}{2}·m·{}^{j\left\{{\omega }_2\left(t+{\tau }_3\right)+{\theta }_2\right\}}& \left(\mathrm{Eq}.7\right)\\ s_2^{{\omega }_1}\left(t\right)=\frac{A_2}{2}·m·{}^{j\left\{{\omega }_1\left(t+{\tau }_2\right)+{\theta }_1\right\}}& \left(\mathrm{Eq}.8\right)\\ s_2^{{\omega }_2}\left(t\right)=\frac{A_4}{2}·m·{}^{j\left\{{\omega }_2\left(t+{\tau }_4\right)+{\theta }_2\right\}}& \left(\mathrm{Eq}.9\right)\end{array}$

Path 802 may include a phase difference detector 814 to receive signal S₁ from tone separator 812 and from a tone separator 816 of path 804 corresponding to sensor 116. Phase difference detector 814 may be configured to determine phase difference of arrival φ_Δ12 from signal S₁ as received at sensors 114 and 116.

Phase differences of arrival φ_Δ12 and φ_Δ34 may be represented by the argument of:

$\begin{array}{cc}\begin{array}{c}{\phi }_{\mathrm{\Delta 12}}\propto \arg \left[s_1^{{\omega }_1}\left(t\right)·\mathrm{conj}\left(s_2^{{\omega }_1}\left(t\right)\right)\right]\\ =\arg \left[\frac{A_1A_2}{4}·m^2·{}^{j\left\{{\omega }_1\left(t+{\tau }_1\right)+{\theta }_1\right\}}{}^{-j\left\{{\omega }_1\left(t+{\tau }_2\right)+{\theta }_1\right\}}\right]\\ =\arg \left[\frac{A_1A_2}{4}·m^2·{}^{{\mathrm{j\omega }}_1\left({\tau }_1-{\tau }_2\right)}\right]\end{array}& \left(\mathrm{Eq}.10A\right)\\ \begin{array}{c}{\phi }_{\mathrm{\Delta 34}}\propto \arg \left[s_1^{{\omega }_1}\left(t\right)·\mathrm{conj}\left(s_2^{{\omega }_2}\left(t\right)\right)\right]\\ =\arg \left[\frac{A_3A_4}{4}·m^2·{}^{j\left\{{\omega }_2\left(t+{\tau }_3\right)+{\theta }_2\right\}}{}^{-j\left\{{\omega }_2\left(t+{\tau }_4\right)+{\theta }_2\right\}}\right]\\ =\arg \left[\frac{A_3A_4}{4}·m^2·{}^{{\mathrm{j\omega }}_2\left({\tau }_3-{\tau }_4\right)}\right]\end{array}& \left(\mathrm{Eq}.11A\right)\end{array}$

Phase differences of arrival φ_Δ12 and φ_Δ34 may be calculated as:

φ_Δ12=ω₁(τ₁−τ₂)  (Eq. 10B)

φ_Δ34=ω₂(τ₃−τ₄)  (Eq. 11B)

System 118 may include a difference converter 818 to convert phase differences of arrivals to corresponding distance differences.

Phase difference of arrivals φ_Δ12 and φ_Δ34 in equations 10 and 11, may be converted to corresponding distance differences Δ_L12 and Δ_L34 as:

$\begin{array}{cc}{\Delta }_{L12}=L_1-L_2=\frac{{\phi }_{\mathrm{\Delta 12}}}{{\omega }_1}v;\mathrm{and}& \left(\mathrm{Eq}.12\right)\\ {\Delta }_{L34}=L_3-L_4=\frac{{\phi }_{\mathrm{\Delta 34}}}{{\omega }_2}v.& \left(\mathrm{Eq}.13\right)\end{array}$

where ν is the speed of light.

FIG. 9 is a graphic illustration of geometries illustrated in FIGS. 1 and 7, presented in an x-y plane.

Distances L₁, L₂, L₃, and L₄, may be represented as:

L ₁ ² =X _A ²+(Y_A−Y_B−D)²  (Eq. 14)

L ₂ ² =X _A ²+(Y_B+D)²  (Eq. 15)

L ₃ ² =X _A ²+(Y_A−Y_B)²  (Eq. 16)

L ₄ ² =X _A ² +Y _B ²  (Eq. 17)

Distance differences Δ_L12 and Δ_L34 may be represented as:

Δ_L12=L₁−L₂=√{square root over (X_A²+(Y_A−Y_B−D)²)}−√{square root over (X_A²+(Y_b+D)²)}  (Eq. 18)

Δ_L34=L₃−L₄=√{square root over (X_A²+(Y_A−Y_B)²)}−√{square root over (X_A²+Y_B²)}  (Eq. 19)

Equations 18 and 19 may be rearranged as:

Δ_L12+√{square root over (X_A²+(Y_B+D)²)}=√{square root over (X_A²+(Y_A−Y_B−D)²)}  (Eq. 20)

Δ_L34+√{square root over (X_A²+Y_B²)}=√{square root over (X_A²+(Y_A−Y_B)²)}  (Eq. 21)

Both sides of equations 20 and 21 may be squared, and resulting terms may be expanded and cancelled to provide, respectively:

Δ_L12²+2Δ_L12√{square root over (X_A²+(Y_B+D)²)}=Y_A²−2Y_AY_B−2DY_A  (Eq. 22)

Δ_L34²+2Δ_L34√{square root over (X_A²+Y_B²)}=Y_A²−2Y_AY_B  (Eq. 23)

Square root terms of equations 22 and 23 may be separated from other terms to provide, respectively:

$\begin{array}{cc}\sqrt{X_A^2+{\left(Y_B+D\right)}^2}=\frac{Y_A^2-2Y_AY_B-2{\mathrm{DY}}_A-{\Delta }_{L12}^2}{2{\Delta }_{L12}}& \left(\mathrm{Eq}.24\right)\\ \sqrt{X_A^2+Y_B^2}=\frac{Y_A^2-2Y_AY_B-{\Delta }_{34}^2}{2{\Delta }_{L34}}& \left(\mathrm{Eq}.25\right)\end{array}$

Both sides of equations 24 and 25 may be squared, and resulting terms may be expanded and rearranged to provide, respectively:

$\begin{array}{cc}{X}_A^2+Y_B^2={\left(\frac{Y_A^2-2Y_AY_B-2{\mathrm{DY}}_A-{\Delta }_{L12}^2}{2{\Delta }_{L12}}\right)}^2-2{\mathrm{DY}}_B-D^2& \left(\mathrm{Eq}.26\right)\\ X_A^2+Y_B^2={\left(\frac{Y_A^2-2Y_AY_B-{\Delta }_{L34}^2}{2{\Delta }_{L34}}\right)}^2& \left(\mathrm{Eq}.27\right)\end{array}$

Equations 26 and 27 may be set equal to one another as:

$\begin{array}{cc}{\left(\frac{Y_A^2-2Y_AY_B-2DY_A-{\Delta }_{L12}^2}{2{\Delta }_{L12}}\right)}^2-2DY_B-D^2={\left(\frac{Y_A^2-2Y_AY_B-{\Delta }_{L34}^2}{2{\Delta }_{L34}}\right)}^2& \left(\mathrm{Eq}.28\right)\end{array}$

Terms of equation 28 may be expanded as:

$\begin{array}{cc}\left(\frac{\begin{array}{c}{Y}_A^4+4Y_A^2Y_B^2+4D^2Y_A^2+{\Delta }_{12}^4-4Y_A^3Y_B-4{\mathrm{DY}}_A^3-\\ 2Y_A^2{\Delta }_{L12}^2+8Y_A^2Y_BD+4Y_AY_B{\Delta }_{L12}^2+4{\mathrm{DY}}_A{\Delta }_{L12}^2\end{array}}{4{\Delta }_{L12}^2}\right)-2{\mathrm{DY}}_B-D^2=\left(\frac{Y_A^4+4Y_A^2Y_B^2+{\Delta }_{L34}^4-4Y_A^3Y_B-2Y_A^2{\Delta }_{L34}^2+4Y_AY_B{\Delta }_{L34}^2}{4{\Delta }_{L34}^2}\right)& \left(\mathrm{Eq}.29\right)\end{array}$

Equation 29 may be rearranged in the form of a quadratic equation:

AY _B ² +BY _B +C=0  (Eq. 30)

where:

$\begin{array}{cc}A=Y_A^2\left(\frac{1}{{\Delta }_{L12}^2}-\frac{1}{{\Delta }_{L34}^2}\right);& \left(\mathrm{Eq}.31\right)\\ B=\left(\frac{-Y_A^3+2Y_A^2D+Y_A{\Delta }_{L12}^2}{{\Delta }_{L12}^2}\right)-2D-\left(\frac{-Y_A^3+Y_A{\Delta }_{L34}^2}{{\Delta }_{L34}^2}\right);& \left(\mathrm{Eq}.32\right)\\ C=\left(\frac{Y_A^4+4D^2Y_A^2+{\Delta }_{12}^4-4{\mathrm{DY}}_A^3-2Y_A^2{\Delta }_{L12}^2+4{\mathrm{DY}}_A{\Delta }_{L12}^2}{4{\Delta }_{L12}^2}\right)-D^2-\left(\frac{Y_A^4+{\Delta }_{L34}^4-2Y_A^2{\Delta }_{L34}^2}{4{\Delta }_{L34}^2}\right)& \left(\mathrm{Eq}.33\right)\end{array}$

Terms A, B and C are defined in terms of known quantities, and Y_B may be solved as:

$\begin{array}{cc}{Y}_B=\frac{-B\pm \sqrt{B^2-4AC}}{2A}& \left(\mathrm{Eq}.34A\right)\end{array}$

A determination as to whether to use the positive or negative value of the square root term in equation 34A may be based on whether Δ_L12 is greater than or less than Δ_L34.

Where Δ_L12·Δ_L34>0, the negative value of the square root term of equation 34A may be used, such that:

$\begin{array}{cc}{Y}_B=\frac{-B-\sqrt{B^2-4AC}}{2A}& \left(\mathrm{Eq}.34B\right)\end{array}$

Where Δ_L12·Δ_L34<0, the positive value of square root term of equation 34A may be used, such that:

$\begin{array}{cc}{Y}_B=\frac{-B+\sqrt{B^2-4AC}}{2A}& \left(\mathrm{Eq}.34C\right)\end{array}$

Where Δ_L12 is equal to zero, L₁ and L₂ in FIG. 9 are equal to one another, and Y_B may be determined as disclosed below with respect to FIG. 10.

FIG. 10 is a graphic depiction of the geometries of FIG. 9, for a situation where L₁=L₂. As illustrated in FIG. 10:

$\begin{array}{cc}{Y}_B=\frac{Y_A}{2}-D& \left(\mathrm{Eq}.34D\right)\end{array}$

Where Δ_L34 is equal to zero, L₃ and L₄ of FIG. 9 are equal to one another, and Y_B may be determined as disclosed below with respect to FIG. 11.

FIG. 11 is a graphic depiction of the geometries of FIG. 9, for a situation where L₃=L₄. As illustrated in FIG. 11:

$\begin{array}{cc}{Y}_B=\frac{Y_A}{2}& \left(\mathrm{Eq}.34E\right)\end{array}$

Given Y_B, equation 27 may be rearranged to solve for X_A:

$\begin{array}{cc}{X}_A=\pm \sqrt{{\left(\frac{Y_A^2-2Y_AY_B-{\Delta }_{L34}^2}{2{\Delta }_{34}}\right)}^2-Y_B^2}& \left(\mathrm{Eq}.35\right)\end{array}$

Due to the directionality of sensors 114 and 116, equations 35 may be solved for X_A using the negative of the square root term of equation 35.

Where L₃=L₄ and Δ_L34=0, as illustrated in FIG. 11, two triangles may be identified having respective hypotenuses of L₁ and L₂, as described below with respect to FIGS. 129 and 13.

FIG. 12 is a graphic depiction of a triangle 1200 having a hypotenuse L₁.

FIG. 13 is a graphic depiction of a triangle 1300 having a hypotenuse L₂.

From the geometries of FIGS. 9 and 10, L₁ and L₂ may be represented as:

$\begin{array}{cc}{L}_1^2=X_A^2+{\left(D-\frac{Y_A}{2}\right)}^2& \left(\mathrm{Eq}.36\right)\\ L_2^2=X_A^2+{\left(D+\frac{Y_A}{2}\right)}^2& \left(\mathrm{Eq}.37\right)\end{array}$

Distance difference Δ_L12, which may be determined as described above, may thus be represented as:

$\begin{array}{cc}{\Delta }_{L12}=L_1-L_2=\sqrt{X_A^2+{\left(D-\frac{Y_A}{2}\right)}^2}-\sqrt{X_A^2+{\left(D+\frac{Y_A}{2}\right)}^2}& \left(\mathrm{Eq}.38\right)\end{array}$

Terms of equation 38 may be rearranged as:

$\begin{array}{cc}\sqrt{X_A^2+{\left(D+\frac{Y_A}{2}\right)}^2}+{\Delta }_{L12}=\sqrt{X_A^2+{\left(D-\frac{Y_A}{2}\right)}^2}& \left(\mathrm{Eq}.39\right)\end{array}$

Both sides of equation 39 may squared, and resultant terms may be rearranged and cancelled, to provide:

$\begin{array}{cc}\sqrt{X_A^2+{\left(D+\frac{Y_A}{2}\right)}^2}=\frac{-2Y_AD-{\Delta }_{L12}^2}{2{\Delta }_{L12}}.& \left(\mathrm{Eq}.40\right)\end{array}$

Both sides of equation 40 may be squared, and resultant terms may be rearranged to solve for X_A when Δ_L34=0, as:

$\begin{array}{cc}{X}_A=\sqrt{{\left(\frac{2Y_AD+{\Delta }_{L12}^2}{2{\Delta }_{L12}}\right)}^2-{\left(D+\frac{Y_A}{2}\right)}^2}& \left(\mathrm{Eq}.41\right)\end{array}$

In FIG. 8, system 118 may include a perpendicular offset calculator 822 to calculate perpendicular offset distance Y_B from distance differences Δ_L12, Δ_L34, and distances D and Y_A, such as described above with respect to one or more of equations 34A through 34E.

System 118 may further include a linear distance calculator 824 to calculate linear distance X_A from a combination of distance differences Δ_L12 and Δ_L34, perpendicular offset distance Y_B, and distance Y_A, such described above with respect to one or more of equations and 35 and 41.

System 118 may further include a coordinate generator 826 to generate coordinates (−X_A, (Y_B+D)) and (−X_A, Y_B).

FIG. 14 is a graphic depiction of coordinates of car 104 relative to car 102 in the x-y plane. In FIG. 14, the coordinates of car 104 are provided with respect to headlights 110 and 112 of car 104, relative to tail light 116 of car 102. One or more offset values may be incorporated to provide coordinates with respect to one or more other features, such as a width of car 104.

In FIG. 8, system 118 may include a frequency converter 808 to generate a lower frequency image of a detected envelope. Subsequent processing may be performed with respect to the lower frequency image, which may simplify the subsequent processing.

Frequency converter 808 may include a heterodyne frequency converter to mix an envelope tone provided by envelope detector 806 with a local oscillator to generate products of the envelope at heterodyned frequencies. System 118 may further include a relatively low pass filter 810 to filter unwanted products, and to provide a relatively low frequency image of the envelope tone to tone separator 812.

Where frequency converter 808 receives a signal as represented in equation 2 above, LPF 810 may provide an output in the form of:

$\begin{array}{cc}{s}_{\mathrm{ik}}\left(t\right)=A_j·m·\cos \left({\omega }_k\left(t+{\tau }_j\right)+{\theta }_k\right)·\cos \left({\omega }_Ot+{\theta }_O\right)\stackrel{\mathrm{lpf}}{=}\frac{A_j·m}{2}·\cos \left\{\left({\omega }_k-{\omega }_O\right)t+{\omega }_k{\tau }_j+\left({\theta }_k-{\theta }_O\right)\right\}& \left(\mathrm{Eq}.42\right)\end{array}$

Equation 42 may be expressed using upper sideband complex sinusoids, such as with digital signal processing, as:

$\begin{array}{cc}{s}_{\mathrm{ik}}\left(t\right)=\frac{A_j}{4}·m·{}^{j\left\{\left({\omega }_k-{\omega }_O\right)t+{\omega }_k{\tau }_j+\left({\theta }_k-{\theta }_O\right)\right\}}& \left(\mathrm{Eq}.43\right)\end{array}$

The complex signal at either of sensors 114 and 116, corresponding to signals S₁ and S₂, may be represented as:

$\begin{array}{cc}{s}_1\left(t\right)=\frac{A_1}{4}·m·{}^{j\left\{\left({\omega }_1-{\omega }_O\right)t+{\omega }_1{\tau }_1+\left({\theta }_1-{\theta }_O\right)\right\}}+\frac{A_3}{4}·m·{}^{j\left\{\left({\omega }_2-{\omega }_O\right)t+{\omega }_2{\tau }_1+\left({\theta }_2-{\theta }_O\right)\right\}}& \left(\mathrm{Eq}.44\right)\\ s_2\left(t\right)=\frac{A_2}{4}·m·{}^{j\left\{\left({\omega }_1-{\omega }_O\right)t+{\omega }_1{\tau }_2+\left({\theta }_1-{\theta }_O\right)\right\}}+\frac{A_4}{4}·m·{}^{j\left\{\left({\omega }_2-{\omega }_O\right)t+{\omega }_2{\tau }_4+\left({\theta }_2-{\theta }_O\right)\right\}}& \left(\mathrm{Eq}.45\right)\end{array}$

Tone separators 812 and 816 may each separate signals S₁ and S₂ from corresponding inputs, such as with DSP-based band pass filtering or FFT processing, to provide:

$\begin{array}{cc}{s}_1^{{\omega }_1}\left(t\right)=\frac{A_1}{4}·m·{}^{j\left\{\left({\omega }_1-{\omega }_O\right)t+{\omega }_1{\tau }_1+\left({\theta }_1-{\theta }_O\right)\right\}}& \left(\mathrm{Eq}.46\right)\\ s_1^{{\omega }_2}\left(t\right)=\frac{A_3}{4}·m·{}^{j\left\{\left({\omega }_2-{\omega }_O\right)t+{\omega }_2{\tau }_1+\left({\theta }_2-{\theta }_O\right)\right\}}& \left(\mathrm{Eq}.47\right)\\ s_2^{{\omega }_1}\left(t\right)=\frac{A_2}{4}·m·{}^{j\left\{\left({\omega }_1-{\omega }_O\right)t+{\omega }_1{\tau }_2+\left({\theta }_1-{\theta }_O\right)\right\}}& \left(\mathrm{Eq}.48\right)\\ s_2^{{\omega }_2}\left(t\right)=\frac{A_4}{4}·m·{}^{j\left\{\left({\omega }_2-{\omega }_O\right)t+{\omega }_2{\tau }_4+\left({\theta }_2-{\theta }_O\right)\right\}}& \left(\mathrm{Eq}.49\right)\end{array}$

Phase difference detectors 814 and 820 may be configured to determine corresponding phase differences of arrival φ_Δ12 and φ_Δ34 as:

$\begin{array}{cc}{\phi }_{\Delta 12}\propto \arg \left[s_1^{{\omega }_1}\left(t\right)\mathrm{conj}\left(s_2^{{\omega }_1}\left(t\right)\right)\right]=\arg \left[\begin{array}{c}\frac{A_1A_2}{16}·m^2·{}^{j\left\{\left({\omega }_1-{\omega }_O\right)t+{\omega }_1{\tau }_1+\left({\theta }_1-{\theta }_O\right)\right\}}\\ {}^{-j\left\{\left({\omega }_1-{\omega }_O\right)t+{\omega }_1{\tau }_2+\left({\theta }_1-{\theta }_O\right)\right\}}\end{array}\right]=\arg \left[\frac{A_1A_2}{16}·m^2·{}^{{\mathrm{j\omega }}_1\left({\tau }_1-{\tau }_2\right)}\right]& \left(\mathrm{Eq}.50A\right)\\ {\phi }_{\Delta 34}\propto \arg \left[s_1^{{\omega }_2}\left(t\right)\mathrm{conj}\left(s_2^{{\omega }_2}\left(t\right)\right)\right]=\arg \left[\begin{array}{c}\frac{A_3A_4}{16}·m^2·{}^{j\left\{\left({\omega }_2-{\omega }_O\right)t+{\omega }_2{\tau }_1+\left({\theta }_2-{\theta }_O\right)\right\}}\\ {}^{-j\left\{\left({\omega }_2-{\omega }_O\right)t+{\omega }_2{\tau }_4+\left({\theta }_2-{\theta }_O\right)\right\}}\end{array}\right]=\arg \left[\frac{A_3A_4}{16}·m^2·{}^{{\mathrm{j\omega }}_2\left({\tau }_3-{\tau }_4\right)}\right]& \left(\mathrm{Eq}.51A\right)\end{array}$

Phase differences of arrival φ_Δ12 and φ_Δ34 may be calculated as:

φ_Δ12=ω₁(τ₁−τ₂)  (Eq. 50B)

φ_Δ34=ω₂(τ₃−τ₄)  (Eq. 51B)

As illustrated by equations above, heterodyning the modulation tones to a lower frequency may be performed substantially without distorting the modulation tones.

Considerations of the frequency of baseband tones ω₁ and ω₂ are now addressed.

A relatively high frequency baseband tone may provide greater accuracy than lower frequency tones.

Anti-phase-aliasing considerations may call for relatively lower frequencies. For example, equation 10 illustrates a relationship between phase difference of arrival φ_Δ12, τ₁ and τ₂, and frequency ω₁. FIG. 14 illustrates a relationship between phase difference of arrival φ_Δ34, τ₃ and τ₄, and frequency ω₂. To avoid phase aliasing, phase differences of arrival φ_Δ12 and φ_Δ34 should be constrained to not exceed π radians.

The largest phase delta may correspond to τ₁=0 and τ₄=0, such as where X_A is zero, in which case τ₂ and τ₃ are determined by a difference between distances D and Y_A. Where system 102 and object 104 correspond to automobiles, and where traffic lanes are at least approximately 3 meters wide, a maximum delay for τ₂ and τ₃ may be set to approximately 10 nano second (ns), which corresponds to:

$\begin{array}{cc}{\omega }_i<\frac{2\pi }{20e-9}& \left(\mathrm{Eq}.52\right)\end{array}$

or a frequency less than approximately 50 MHz.

FIG. 15 is a process flowchart of a method 1500 of determining multi-dimensional positions of objects based on propagation delay differences of multiple signals received at multiple sensors. Method 1500 may be implemented such as described above with respect to system 118. Method 1500 is not, however, limited to the example of system 118.

At 1502, first and second signals, from corresponding first and second transmitters, are received at each of first and second sensors. The first and second signals may include one or more of optical signals, optical signals in a visible spectrum, RF signals, and modulated signals, including amplitude modulated signals, such as described in one or more examples above. The first and second transmitters may have a fixed distance therebetween, and the first and second sensors may have a fixed distance therebetween. The first and second transmitters, and/or the first and second sensors, may be affixed to an object, which may include a movable object, such as a automobile, water craft, or aircraft.

At 1504, a first phase difference of arrival is determined with respect to the first signal received at the first sensor and the first signal received at the second sensor.

At 1506, a second phase difference of arrival is determined with respect to the second signal received at the first sensor and the second signal received at the second sensor.

The first and second phase differences of arrival may be determined in accordance with equations 10B and 11B.

At 1508, the first and second phase differences of arrival are converted to corresponding first and second distance differences.

At 1510, a linear distance and a perpendicular offset distance are determined, between a point proximate to the first and second sensors and a point proximate to the first and second transmitters. The perpendicular offset distance may be determined in accordance with one or more of equations 34A through 34E. The linear distance may be determined in accordance with one or more of equations 35 and 41.

Method 1500 may be implemented to generate two-dimensional planar coordinates and/or to generate coordinates in multiple planes. For example, the perpendicular offset distance may correspond to one or more of a lateral offset distance, vertical offset distance, a diagonal offset distance, and combinations thereof.

One or more features disclosed herein may be implemented in hardware, software, firmware, and combinations thereof, including discrete and integrated circuit logic, application specific integrated circuit (ASIC) logic, and microcontrollers, and may be implemented as part of a domain-specific integrated circuit package, or a combination of integrated circuit packages. The term software, as used herein, refers to a computer program product including a computer readable medium having computer program logic stored therein to cause a computer system to perform one or more features and/or combinations of features disclosed herein.

In FIG. 1, system 118 may be implemented with integrated circuit logic, a computer system configured with appropriate software, and combinations thereof.

FIG. 16 is a block diagram of a computer system 1600, including one or more computer instruction processing units, illustrated here as a processor 1602, to execute computer program product logic, also known as instructions, code, and software.

As described below, computer system 1600 is configured to determine multi-dimensional positions of objects based on propagation delay differences of multiple signals received at multiple sensors.

Computer system 1600 includes memory/storage 1604, including a computer readable medium having computer program product logic or instructions 1606 stored thereon to cause processor 1602 to perform one or more functions in response thereto.

Memory/storage 1604 further includes data 1608 to be used by processor 1602 in executing instructions 1606, and/or generated by processor 1602 in response to execution of instructions 1606.

Logic 1606 includes difference converter logic 1610 to cause processor 1602 to convert phase difference of arrival values 1612 to distance difference values 1614, such as described in one or more examples above.

Computer system 1600 may be configured to receive phase difference of arrival values 1612 from a phase difference detector, such as described above with respect to 814 in FIG. 8, which may be implemented within integrated circuitry.

Alternatively, computer system 1600 may include phase difference detector logic to cause processor 1602 to generate phase difference of arrival values 1612. Computer system 1600 may further include tone separator logic to cause processor 1602 to separate tones from an envelope, such as described above with respect to tone separator 812 in FIG. 8.

Alternatively, difference converter logic 1610 may be implemented within integrated circuitry, and computer system 1600 may be configured to receive distance difference values 1614 from such circuitry.

Logic 1606 further includes perpendicular offset logic 1622 to cause processor 1602 to determine a perpendicular offset distance 1624 from a combination of distance difference values 1614, a transmitter distance 1618, and a sensor distance 1620, such as described in one or more examples above. Perpendicular offset logic 1622 may include logic to determine perpendicular offset distance 1624 in accordance with one or more of equations 34A through 34E.

Logic 1606 further includes linear distance logic 1626 to cause processor 1602 to determine a linear distance 1628 from a combination of distance difference values 1614, perpendicular offset distance 1624, and transmitter distance 1618, such as described in one or more examples above. The linear distance logic 1626 may include logic to determine linear distance 1628 in accordance with one or more of equations 35 and 41.

Logic 1606 further includes coordinate generator logic 1630 to cause processor 1602 to generate coordinates 1632 corresponding to a relative position of an object based on perpendicular offset distance 1624 and linear distance 1628. Coordinates 1632 include at least two-dimensional planar coordinates, and may include coordinates in more than two dimensions.

Computer system 1600 may include a communications infrastructure 1640 to provide one or more communication paths within computer system 1600.

Computer system 1600 may include an input/output (I/O) controller 1642 to provide one or more communication paths between computer system 1600 and one or more other systems and/or communication systems.

Methods and systems disclosed herein may be implemented to provide discrete snap-shots of a position of an object. Multiple discrete Snap-shots may be tracked over to provide motion or movement information, such as for traffic monitoring and/or control, or trajectory analysis, such as with respect to security or collision detection/avoidance.

Methods and systems are disclosed herein with the aid of functional building blocks illustrating the functions, features, and relationships thereof. At least some of the boundaries of these functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternate boundaries may be defined so long as the specified functions and relationships thereof are appropriately performed.

Claims

1. A method, comprising: receiving first and second signals from corresponding first and second transmitters, at each of first and second sensors; anddetermining at least two-dimensional coordinates from a phase difference of arrival of the first signal at the first and second sensors, a phase difference of arrival of the second signal at the first and second sensors, a distance between the first and second transmitters, and a distance between the first and second sensors;wherein the determining is performed within one or more of circuitry and a suitably programmed computer system.

2. The method of claim 1, wherein the determining includes: determining a first phase difference of arrival with respect to the first signal received at the first and second sensors, and a second phase difference of arrival with respect to the second signal received at the first and second sensors;determining first and second distance differences from the corresponding first and second phase differences of arrival; anddetermining a linear distance and perpendicular offset distance from a combination of the first and second distance differences, a distance between the first and second transmitters, and a distance between the first and second sensors.

3. The method of claim 2, wherein the determining of the linear distance and the perpendicular offset distance includes: determining the perpendicular offset distance from a combination of the first and second distance differences, the distance between the first and second transmitters, and the distance between the first and second sensors; anddetermining the linear distance from a combination of the perpendicular offset distance, the first and second distance differences, and the distance between the first and second sensors.

4. The method of claim 2, wherein the determining of the perpendicular offset distance includes: determining the perpendicular offset distance using a first computation when the product of the first distance difference and the second distance difference is greater than zero; anddetermining the perpendicular offset distance using a second computation when the product of the first distance difference and the second distance difference is less than zero.

5. The method of claim 2, wherein the determining of the perpendicular offset distance includes: determining the perpendicular offset distance as one half of the distance between the first and second sensors, minus the distance between the first and second transmitters, when the first distance difference is equal to zero; anddetermining the perpendicular offset distance as one half of the distance between the first and second sensors when the second distance difference is equal to zero.

6. The method of claim 2, wherein the determining of the linear distance includes: determining the linear distance independent of the perpendicular offset distance when the second distance difference is equal to zero.

7. The method of claim 1, wherein the receiving includes: receiving first and second amplitude modulated optical signals at each of first and second optical sensors.

8. The method of claim 2, wherein the determining of the perpendicular offset distance includes determining a lateral offset distance and a vertical offset distance.

9. A system, comprising: first and second sensors, each to receive a first signal from a first transmitter and a second signal from a second transmitter; anda computation system to determine at least two-dimensional coordinates from a phase difference of arrival of the first signal at the first and second sensors, a phase difference of arrival of the second signal at the first and second sensors, a distance between the first and second transmitters, and a distance between the first and second sensors.

10. The system of claim 9, wherein the computation system includes: a phase difference detector to determine a first phase difference of arrival with respect to the first signal received at the first and second sensors, and to determine a second phase difference of arrival with respect to the first second received at the first and second sensors;a difference converter to convert the first and second phase differences of arrival to corresponding first and second distance differences; anda calculator system to determine a linear distance and perpendicular offset distance from a combination of the first and second distance differences, a distance between the first and second transmitters, and a distance between the first and second sensors.

11. The system of claim 10, wherein the calculator system includes: a perpendicular offset calculator to determine the perpendicular offset distance from a combination of the first and second distance differences, the distance between the first and second transmitters, and the distance between the first and second sensors; anda linear distance calculator to determine the linear distance from a combination of the perpendicular offset distance, the first and second distance differences, and the distance between the first and second sensors.

12. The system of claim 10, wherein the calculator system includes a perpendicular offset calculator to: determine the perpendicular offset distance as one half of the distance between the first and second sensors, minus the distance between the first and second transmitters, when the first distance difference is equal to zero; anddetermine the perpendicular offset distance as one half of the distance between the first and second sensors when the second distance difference is equal to zero.

13. The system of claim 9, wherein the first and second sensors include first and second optical sensors to receive and convert amplitude modulated optical signals and to electrical signals.

14. The system of claim 9, wherein the calculator system is configured to generate at least three-dimensional coordinates.

15. The system of claim 9, further including: an automobile configured to house the first and second sensors.

16. The system of claim 9, further including: an automobile configured to house the first and second transmitters.

17. A computer program product including a computer readable medium having computer program logic stored therein, the computer program logic comprising: receive logic to cause a processor to receive information corresponding to first and second signals received at each of first and second sensors from corresponding first and second transmitters; andcomputation logic to cause the processor to determine at least two-dimensional coordinates from a phase difference of arrival of the first signal at the first and second sensors, a phase difference of arrival of the second signal at the first and second sensors, a distance between the first and second transmitters, and a distance between the first and second sensors.

18. The computer program product of claim 17, wherein the computation logic includes: perpendicular offset logic to cause the processor to determine a perpendicular offset distance from a combination of, a first distance difference corresponding to a propagation delay time difference of the first signal received at first and second sensors,a second distance difference corresponding to a propagation delay time difference of the second signal received at the first and second sensors,a distance between the first and second transmitters, anda distance between the first and second sensors; anda linear distance logic to cause the processor to determine a linear distance from a combination of the perpendicular offset distance, the first and second distance differences, and the distance between the first and second sensors.

19. The computer program product of claim 18, wherein the perpendicular offset logic includes: logic to cause the processor to determine the perpendicular offset distance using a first computation when the product of the first distance difference and the second distance difference is greater than zero; andlogic to cause the processor to determine the perpendicular offset distance using a second computation when the product of the first distance difference and the second distance difference is less than zero.

20. The computer program product of claim 18, wherein the perpendicular offset logic includes: logic to cause the processor to determine the perpendicular offset distance as one half of the distance between the first and second sensors, minus the distance between the first and second transmitters, when the first distance difference is equal to zero; andlogic to cause the processor to determine the perpendicular offset distance as one half of the distance between the first and second sensors when the second distance difference is equal to zero.