The present disclosure is related to LiDAR systems and, in particular, to a LiDAR system using synthetic Doppler processing, which can be used in an automotive or other applications.
LiDAR is commonly referred to as an acronym for light detection and ranging, in the sense that LiDAR is commonly considered an optical analog to radar. In general, there are two types of LiDAR systems, namely, incoherent LiDAR and coherent LiDAR. Incoherent LiDAR, also commonly referred to as direct detection or direct energy detection LiDAR, primarily uses an amplitude measurement in light returns, while coherent LiDAR is better suited for phase-sensitive measurements or other more sophisticated transmitter waveform modulation techniques. Coherent systems generally use optical heterodyne detection, which, being more sensitive than direct detection, allows them to operate at a much lower power and provide greater measurement accuracy and resolution, but at the expense of more complex transceiver requirements and cost.
According to a first aspect, a detection system is provided. The detection system includes a signal transmitter for transmitting transmitted signals into a region and a receiver for receiving reflected signals generated by reflection of the transmitted signals and for generating receive signals indicative of the reflected signals. A processor coupled to the receiver receives the receive signals and processes the receive signals to generate detections of one or more objects in the region. The processing includes altering phase shift to generate phase-modulated signals from the receive signals and generating the detections from the phase-modulated signals.
The phase shift can be altered by a phase modulator, the phase modulator altering phase shift in a local oscillator (LO) signal. Alternatively, the phase shift can be altered by altering an output of a direct digital synthesizer (DDS) utilized in generating the transmitted signals and the receive signals. The phase shift can be altered by adding a phase shift value to in-phase and quadrature-phase detector signals generated from the receive signals. The phase shift value can be numerically indexed.
The frequency of the transmitted signals can be controlled to vary according to a ramp between a first frequency and a second frequency. The ramp can be a linear ramp. The ramp can have a slope such that the first frequency is lower than the second frequency or the first frequency is higher than the second frequency.
The transmitted signals can be frequency-modulated continuous-wave (FMCW) signals. Alternatively, the transmitted signals can be pulsed signals.
The signal transmitter can angularly scan the transmitted signals into the region at varying angles. In some embodiments, the signal transmitter comprises a scanning mirror for scanning the transmitted signals at varying angles into the region. The scanning mirror can be a micro-electromechanical (MEMS) scanning mirror.
The detection system can be an automotive detection system.
In some exemplary embodiments, the detection system is a radar system. In these embodiments, the signal transmitter is a radar signal transmitter, the transmitted signals are transmitted radar signals, and the reflected signals are reflected radar signals.
In some exemplary embodiments, the detection system is a radar system. In these embodiments, the signal transmitter is a radar signal transmitter, the transmitted signals are transmitted radar signals, and the reflected signals are reflected radar signals.
At least one of the one or more objects can be stationary with respect to the detection system. Alternatively, or additionally, at least one of the one or more objects is in motion with respect to the detection system.
The present disclosure is further described in the detailed description which follows, in reference to the noted plurality of drawings by way of non-limiting examples of embodiments of the present disclosure, in which like reference numerals represent similar parts throughout the several views of the drawings.
Direct detection LiDAR systems are characterized by construction and functional simplicity and, unlike the more complex homodyne or heterodyne LiDAR systems, do not utilize frequency translation or down conversion stages, which facilitate signal detection and processing gain advantages. The signal detection and processing gain advantages of homodyne/heterodyne LiDAR systems are enabled by advanced modulation and coding of the transmitted signal combined with sophisticated correlation processing techniques within the LiDAR receiver. Transmit signal modulation and coding, in conjunction with advanced correlation processing techniques, have been utilized within radar systems, from complex military object imaging systems to commercial automotive autonomous cruise control applications. LiDAR systems, with the exception of very advanced measurement requirements, e.g. NASA measurements of CO2 emissions, have not utilized these techniques. However, according to the present disclosure, development of laser transmit signal envelope modulation and quadrature demodulation of the recovered envelope modulation signal has exhibited similar advantages to those associated and achieved via the radar science. Laser transmitter envelope modulation and quadrature demodulation represent a modest increase in complexity of direct detection LiDAR systems with significant benefits in measurement capability and lower operational power by enabling signal processing gain to direct detection LiDAR.
According to the exemplary embodiments described herein in detail, laser transmitter envelope modulation and receiver quadrature demodulation techniques are applied to direct detection LiDAR systems. Specific transmitter modulation envelope waveforms, e.g., pulse burst and frequency modulated continuous wave (FMCW) are described in detail. Data acquisition techniques and processing gain are also described herein in detail. Specific measurement enhancements and parameters associated with each envelope modulation waveform are also described in detail.
Mod(t)=sin(2πfmt)→modulation waveform
Car(t)=sin(2πfct)→carrier
Tx(t)=Mod(t)·Car(t)→envelop modulated carrier (1)
It is noted that the envelope-modulated carrier implies multiplication of the modulation waveform and the carrier signal. The direct detection LiDAR system performs the multiplication within the laser modulator element as described below in detail. Unlike other systems which use a modulated carrier, the envelope modulation technique results in transmission of both sidebands.
It should be noted that, in accordance with exemplary embodiments, the position in time of the modulating pulses may be a variable, which allows for pulse position modulation (PPM) coding.
One principle of transmitter envelope modulation is that upon transmission, the modulation envelope is subject to phase delay in accordance with the envelope frequency. The total transmission phase shift in the two-way range from LiDAR system to object is described by the following equation (2):
In exemplary embodiments, upon envelope recovery in a photo-diode, or photodetector or light detector, as described below in detail, the amplitude and transmission phase of the modulation envelope are demodulated in the quadrature demodulator.
In contrast with the envelop-modulated/quadrature-demodulation direct-detection LiDAR approach of the exemplary embodiments,
In addition to the above described direct detection LiDAR system 50, a time-of-flight (TOF) system transmits multiple pulses in the form of a square-wave and utilizes a phase detector on receive to measure the two-way time of flight. The time-of-flight system must limit the square-wave modulation frequency in order to avoid phase ambiguity.
Referring to
The optical signal used to illuminate the one or more target objects is generated by a signal generator 182. The output signal of signal generator 182, which in exemplary embodiments is a continuous substantially sinusoidal signal, is applied to a power splitter 184, which splits the signal and provides the split signal at two outputs. The first output 185 is routed to splitting and phase shifting circuitry or 90-degree power splitter 186, which splits the signal, applies a phase shift to one of the resulting split signals, and generates a pair of output signals being offset in phase. In exemplary embodiments, a 90-degree phase shift is applied to one of the signals, such that splitting and phase shifting circuitry or 90-degree power splitter 186 generates a first “in-phase” local oscillator (LO) signal 189 and a second “quadrature-phase” or “quadrature” LO signal 191, which is shifted in phase by 90 degrees with respect to in-phase LO signal 189. The in-phase and quadrature-phase LO signals 189, 191 are applied to second inputs of I/Q mixers 162, 164, respectively. I/Q mixers 162, 164 mix the amplified and filtered input signal at node 161 with the in-phase and quadrature-phase LO signals 189, 191, respectively, to generate output signals 193, 195, respectively, which are low-pass filtered by low-pass filter (LPF) 166 and LPF 168, respectively. The resulting filtered analog signals are converted to digital signals by analog-to-digital converters (ADC) 170, 172, respectively, and sampled under the control of sample control signal 197, which is generated by digital signal processor and control (DSPC) 168. The resulting sampled digital I/Q (quadrature) signals, i.e., I-channel and Q-channel signals, 105, 107 are processed by DSPC 168 to determine range and/or velocity of the one or more target objects. Results of this detection processing performed by DSPC 168 can be forwarded as desired, such as, for example, to a user interface, via a system interface 109.
Continuing to refer to
Thus, according to exemplary embodiments, the quadrature detection precedes analog-to-digital conversion. The quadrature detector recovers the pulse modulation envelope associated with the low-frequency pulse modulation. The data samples are subsequently processed via spectral resolution or other means of each range bin data set. The spectral resolution approach used reduces the detection bandwidth and effectively integrates the energy of the range bin sample set.
According to the exemplary embodiments, Doppler frequency detection of moving objects within the field of view of LiDAR system 100 is enabled by coherent detection of the change in phase which results from the change in range due to relative velocity between LiDAR system 100 and the target object. Doppler detection is significant because the detection bandwidth reduction associated with Doppler processing increases the signal-to-noise ratio in direct proportion to the bandwidth ratio. Therefore, according to the present disclosure, described below in detail, the synthetic Doppler technique of the disclosure is a means for synthetically inducing “motion” to stationary objects, thereby facilitating 2-D FFT processing.
According to some exemplary embodiments, in addition to Doppler processing, multiple frame range bin sampling may also be used to execute a coherent pulse integration approach which also increases the signal-to-noise ratio in direct proportion to the number of pulses integrated.
Detailed description of data acquisition and signal processing techniques that may be utilized in conjunction with pulse burst envelope modulation LiDAR system 100 with quadrature demodulation is now provided. The first step in the pulse burst envelope modulation LiDAR system signal processing is acquisition of a data set which represents the signal level of each range bin at the output of each channel of the quadrature demodulator from successive transmission pulses.
Referring to
Upon completion of M range bin samples in each of N frames, an M×N data matrix is filled for each channel of the quadrature demodulator. It should be noted that the variable-amplitude range bin pulses result from moving objects that are coherently detected by the quadrature demodulator and enable Doppler frequency measurement via spectral resolution of the range bin samples.
There are two processing approaches available to enhance signal detection via increase to the signal-to-noise ratio: coherent pulse integration and spectral resolution of each column of the data matrix. Each column of the data matrix represents range bin samples taken at discrete time points following transmission of the pulse burst. The approach related to coherent pulse integration is captured within the following equation (4):
In the presence of zero-mean, Gaussian noise, ideal coherent pulse integration improves the signal-to-noise ratio by N, the number of pulses integrated.
Spectral resolution is executed in accordance with the discrete Fourier Transform and the following equation (5):
The FFT is a computationally efficient technique for the calculation of the discrete Fourier Transform, which implements a set of identical filters, or filter bank, distributed uniformly over the frequency domain at intervals of 1/NT, where T is the time interval over which N samples of a waveform have been acquired. This is illustrated in
It is useful to quantify the signal processing gain for the pulse burst LiDAR envelope modulation waveform. Simulation results are documented within the graphic of
According to exemplary embodiments, the direct detection LiDAR described in detail herein can also use FMCW modulation, instead of pulse burst modulation, along with quadrature demodulation.
Referring to
The modulating FM signal is generated by a voltage-controlled oscillator (VCO) 282 under the control of a control signal from phase-locked loop (PLL) control circuit 283, which is in turn controlled by DSPC 268. As illustrated in
Continuing to refer to
Upon incidence with an object within the beam width of transmit antenna 280, the transmitted signal is scattered or reflected, in accordance with the geometric and other physical properties of the object. A fraction of the scattered signal is received by the LiDAR light detector where the FM-modulated envelope is recovered and subsequently amplified by the transimpedance amplifier 258.
The recovered/amplified FM modulation waveform envelop is further processed with band pass filter 260 centered at the arithmetic mean of the frequency limits (f2−f1)/2 and bandwidth commensurate with the envelope modulation frequency limits (f2−f1). Band pass filter 260 rejects extraneous signals as well as broad band noise from TIA 258 and 1/f noise of detector 256 and TIA 258. The received signal propagates to the input of the quadrature demodulator where the difference frequency is detected and applied to ADCs 270, 272. The frequency difference results from the time delay difference between the two-way range time delay and the coherent local oscillator at the input to the quadrature demodulator.
According to exemplary embodiments, coherent detection of the linear FM modulation envelope provides range information in accordance with the graph of
The ADCs 270, 272 acquire samples of the quadrature demodulator output during the linear frequency ramp interval, ΔT; the sample sequence is then subjected to spectral analysis. The spectral analysis approach is generally executed in accordance with the Fast Fourier Transform (FFT), which implements a filter bank of discrete range bins. Each range bin is examined to determine if a signal is present at a specific threshold level.
Data acquisition and signal processing techniques that may be utilized in conjunction with the FMCW envelope modulation LiDAR system and quadrature demodulation, according to some exemplary embodiments, is now described in detail. In addition to the one-dimensional FFT processing described above, a two-dimensional FFT may be executed which further enhances the detection process and provides Doppler frequency detection. Two-dimensional FFT is also described in detail herein, where a processing gain of 24.1 dB is calculated for the 256 point range FFT and 21.1 dB for the 128 point Doppler FFT.
In addition to a single object within the transmit optics beam width, additional objects engender additional IF frequencies directly proportional to the individual object range. A useful technique for the detection of multiple objects uses spectral resolution of the aggregate sampled data. The FFT is a computationally efficient procedure for the calculation of the Discrete Fourier Transform (DFT), which implements a set of identical filters, or a filter bank, distributed uniformly over the frequency domain at intervals of 1/NT, where T is the time interval over which N samples of a waveform have been acquired (also ΔT in this case). The FFT is particularly well suited to IF spectral resolution in FMCW radars because the narrow information bandwidth requires a filter bank which may be implemented numerically with a modest capability digital signal processor. As noted above,
The processing gain of the N-point FFT is given by:
Upon acquisition of I-channel and Q-channel data, the signal processing procedure, e.g., FFT, is executed, and each filter is tested for signal level and compared to a previously established threshold. The threshold test is utilized to determine the presence or absence of an object and may initiate additional techniques of object discrimination.
In addition to the FFT processing of a singular frequency ramp data, referred to as one-dimensional FFT, according to the exemplary embodiments, additional signal processing gain is achieved via the two-dimensional FFT procedure, where sampled data is acquired from multiple frequency ramps in order to extract object relative velocity as related to Doppler frequency and to further reduce the noise detection bandwidth and thereby provide additional processing gain. The two-dimensional FFT uses sampled data from multiple frequency ramps as illustrated in
The two-dimensional FFT process procedure is further illustrated in
Continuing to refer to
Continuing to refer to
Referring to
At the maximum closing velocity, the object range cell dwell time may be written:
The data acquisition time is the time required to fill the data matrix and may be written:
A comparison of the range cell object dwell time and data acquisition time indicates compliance with the condition for optimum processing gain.
The minimum number of range samples affects the range signal processing gain and is limited by the IF frequency at maximum operational range in accordance with the equation:
Therefore, the minimum number of samples may be found via the following equation (15):
Nmin=fif_max·ΔT=128 (15)
It is noted that for additional processing gain, the sample rate may be increased. In that case, ADCs 270, 272 would be capable of the higher sampling rate without compromising performance. For the illustrative exemplary embodiments, the number of samples has been increased to provide greater processing gain, particularly for the condition in which the object straddles an adjacent range bin. The number of samples and the range sampling rate for the illustrative example may now be written:
N=256 samples per frequency ramp
fsR=2.0·106 samples per second (16)
Continuing with the parametric definitions and numerical analysis, the maximum Doppler frequency may be calculated from a knowledge of the nominal envelope modulation wavelength/frequency and the maximum velocity:
In some exemplary embodiments, the modulation frequency is generally limited by the laser modulator, and is typically less than 2 GHz for low cost modulators; although significantly higher frequency laser modulators have been reported.
It is beneficial to calculate the noise detection bandwidth for both range and Doppler parameters, as indicated below in equations (18). The range and Doppler bandwidths are significant in the detection process because the noise level is determined by their values.
It is noted that the ratio of the range sample rate to the Doppler sample rate provides the Doppler processing gain estimate, and is in addition to the range signal processing gain.
The processing gain for the range and Doppler FFT may be estimated using the following equations (19):
PGR_dB=10·log(N)=24.1 dB
PGD_dB=10·log(M)=21.1 dB (19)
Significant elements of the exemplary embodiments include the change in transmission phase shift of the envelope modulation waveform over the two-way range to the object, and coherent detection of the envelop modulation waveform within the quadrature demodulator. The local oscillator for the quadrature demodulator is also the source of the envelope modulation signal.
A fundamental feature of transmitter envelope modulation according to the exemplary embodiments is that upon transmission, the modulation envelope is subject to phase delay in accordance with the envelope modulation frequency. Upon recovery of the modulation envelope in the photo detector diode, the amplitude and transmission phase of the modulation envelope are detected within the quadrature demodulator.
According to the exemplary embodiments, the total transmission phase shift in the two-way range from LiDAR to object is described by the following equation (20):
According to the exemplary embodiments, the mathematical development of Doppler frequency follows:
Throughout the present Detailed Description, embodiments have been described in which the envelope modulation waveform varies linearly with a positive frequency/ramp slope, that is, with the frequency of the envelope modulation increasing with time in a linear ramp function, such as that illustrated in
Furthermore, in addition to the linear ramp FMCW waveforms described in detail herein, the present disclosure is also applicable to other alternate envelope modulation waveforms, which offer some flexibility and in some cases, unique operational advantages. Such alternate envelope modulation waveforms can include, positive/negative linear frequency ramp envelope modulation waveforms, step-frequency ramp envelope modulation waveforms, and pseudo-random envelope frequency modulation (FM) waveforms. Examples of these waveforms are illustrated in
Upon substitution for the variable range, the IF equation may be written:
Therefore, the IF frequency includes two components: a component at the start of the ramp due to the initial range (Ro); and a component due to the change in range due to relative velocity, (v·t). The positive or negative slope of the ramp imparts a positive or negative offset to the IF frequency, which, upon spectral resolution of the acquired data set during each frequency ramp, provides the Doppler frequency. The Doppler frequency has a positive/negative (±) effect dependent on increasing (−) or decreasing (+) range due to velocity.
According to the exemplary embodiments, parametric operational considerations for the step frequency ramp are made. For example, in some exemplary embodiments, the frequency step (Δf) does not exceed the value which engenders a two-way phase shift of greater than 2π at the maximum range of operation. The condition may be mathematically illustrated by the following equations (25):
Also, besides the maximum frequency step increment, the frequency dwells at a fixed value for a time increment greater than the two-way time of flight to the target at the maximum range of operation. Expressed mathematically in equations (26):
Referring to
According to the exemplary embodiments described herein in detail, transmitter envelope modulation and receiver quadrature demodulation techniques are applied to direct detection LiDAR systems. The technique of transmit envelope modulation in conjunction with receive quadrature demodulation as applied to direct detection LiDAR systems is demonstrated to provide signal processing gain as determined by the increase in the signal-to-noise ratio at the system detection stage. Significant operational factors in connection with the exemplary embodiments include the change in transmission phase shift of the envelope modulation waveform over the two-way range to the object, and coherent detection of the envelope modulation waveform within the quadrature demodulator. In addition, in exemplary embodiments, the envelope modulation waveform is derived from the quadrature demodulation local oscillator, thereby establishing the coherent signal used for detection.
The achievement of signal processing gain in direct detection LiDAR systems according to the present disclosure far exceeds the modest increase in hardware complexity. The availability of integrated circuit phase-locked loop and quadrature demodulation functions provides ease of implementation with minimum impact to system volume, operating power and cost. Also, the LiDAR architecture described in detail herein provides systems with lower transmit power, longer measurement range, reduced power consumption and better performance in multiple-system deployment conditions.
According to exemplary embodiments, a synthetic Doppler technique is employed in a scanning LiDAR detection system to achieve additional signal processing gain. The scanning LiDAR implementation can be of the type described in copending U.S. patent application Ser. No. 15/410,158, filed on Jan. 19, 2017, incorporated herein by reference in its entirety. In that copending application, a scanning LiDAR system is described in detail in connection with
In some exemplary embodiments, the LiDAR system can include a microelectromechanical system (MEMS) scanning mirror for enhancing processing of optical signals. MEMS scanning mirrors are one of the technologies for implementation of laser beam scanning. MEMS mirrors are manufactured using semiconductor technology which facilitates high volume manufacturing, repeatable performance and low cost. Additional attributes of the MEMS scanning mirror technology are high tolerance to vibration and operational environment, accurate/rapid scanning, electronic control of scanning mirror position and small volume.
The modulating step-FM signal is generated by a step-FM source, which includes a voltage-controlled oscillator (VCO) 182A under the control of a control signal from phase-locked loop (PLL) control circuit 183A, which is in turn controlled by DSPC 168A via a control signal on line 181A. The output signal of VCO 182A is applied to a power splitter 184A, which splits the signal and provides the split signal at two outputs. The first output 185A is routed to splitting and phase shifting circuitry or 90-degree power splitter 186A, which splits the signal, applies a phase shift to one of the resulting split signals, and generates a pair of output signals being offset in phase. In exemplary embodiments, a 90-degree phase shift is applied to one of the signals, such that splitting and phase shifting circuitry or 90-degree power splitter 186A generates a first “in-phase” local oscillator (LO) signal 189A and a second “quadrature-phase” or “quadrature” LO signal 191A, which is shifted in phase by 90 degrees with respect to in-phase LO signal 189A. The in-phase and quadrature-phase LO signals 189A, 191A are applied to second “L” inputs of I/Q mixers 162A, 164A, respectively. I/Q mixers 162A, 164A mix the amplified and filtered input signal at node 161A applied at first “R” inputs of I/Q mixers 162A, 164A with the in-phase and quadrature-phase LO signals 189A, 191A, respectively, to generate output signals 193A, 195A, respectively, which are low-pass filtered by low-pass filter (LPF) 166A and LPF 168A, respectively. The resulting filtered analog signals are converted to digital signals by analog-to-digital converters (ADC) 170A, 172A, respectively, and sampled under the control of sample control signal 197A, which is generated by DSPC 168A. The resulting sampled digital I/Q (quadrature) signals, i.e., I-channel and Q-channel signals, 105A, 107A are processed by DSPC 168A to determine range and/or velocity of the one or more target objects. Results of this detection processing performed by DSPC 168A can be forwarded as desired, such as, for example, to a user interface, via a system interface 109A.
Continuing to refer to
The timing of pulses in the pulsed sinusoidal signal 111A is controlled by step-FM pulse-burst modulation signal 115A on output signal line 113A from DSPC 268A. That is, step-FM pulse-burst modulation signal 115A is used by pulse modulator 174A to modulate substantially sinusoidal signal 187A to generate pulsed substantially sinusoidal signal 111A. The resulting pulsed modulated signal 111A from pulse modulator 174A is applied as a modulation signal to a laser modulator 176A, which generates a control/modulation signal 117A, which is applied to light emitter 178A to generate a step-FM pulse-burst modulated optical signal. In system 200A, the step-FM pulse-burst modulated optical signal is transmitted to MEMS mirror 210 along optical path 240, where it is reflected by MEMS mirror 210 along optical path 242A to transmit optics 280A, by which the step-FM pulse-burst modulated optical signal is transmitted to the one or more target objects in the transmit beam pattern 282A of MEMS scanning mirror 210A.
Continuing to refer to
Referring to
As noted above, to acquire data accurately at repeatable scanning mirror locations, synchronization between the scanning mirror position and the pulse burst transmission time is implemented, according to some exemplary embodiments. One technique for synchronization is to divide the time between the start and stop position scan signals into many smaller, equal-time increments which approximate the angular position of scanning mirror 210A. The division may be accomplished with a phase-locked loop (PLL) 252A configured as a frequency multiplier. The output of the PLL frequency multiplier 252A is applied to a counter 254A, which acts as a frequency divider. That is, counter 254A output value represents the time of the scan from which the angular position of mirror 210A may be calculated using a cosine function or determined from a look-up table (LUT), as illustrated by 256A. The mirror direction is determined using a D-flip-flop 258A and the synchronized transmission pulse burst is thus generated. Thus, PLL 252A generates a clock from the Mirror Cycle X2 signal. For each scan, which can be either forward or reverse, a single pulse is generated in the Mirror Cycle X2 signal. PLL 252A is configured to divide this single pulse into, for example, 1024 shorter pulses, uniformly spaced in time. These pulses are routed to counter 254A, the current value of which corresponds to the time of the scan. The angular position of scanning mirror 210A can be calculated using the cosine function or determined from a look-up table (LUT), as illustrated by 256A. When combined with the single D flip-flop 258A to monitor the direction of mirror motion, the synchronized train of pulses 215A is generated by DSPC 268A. To that end, the output of D-flip-flop is applied on lines 218A to DSPC 268A, and the output of LUT/cosine function 256A, indicative of mirror position, is also applied on lines 218A to DSPC 268A. The mirror drive signal 212A, also output from LUT/cosine function 256A, is applied on lines 214A to MEMS scanning mirror 210A to control its rotation.
A potential anomaly exists with respect to samples acquired during the negative slope of the scan cycle. For example, in order to reconstruct the samples from the related scan increment, the FFT sample rate can be adjusted. For example, in some particular exemplary embodiments, the FFT sample rate can be adjusted to twice the scan time.
According to the present disclosure, laser transmitter step-FM pulse-burst envelope modulation and receiver quadrature demodulation techniques pursuant to direct detection LiDAR systems have been described in detail. Data acquisition techniques and signal processing gain have also been described in detail. According to the present disclosure, the technique of transmit envelope modulation in conjunction with receive quadrature demodulation as applied to direct detection LiDAR systems has been demonstrated to provide signal processing gain as determined by the increase in the signal-to-noise ratio at the system detection stage. Significant operational factors include the change in transmission phase shift of the envelope modulation waveform over the two-way range to the object, and coherent detection of the envelope modulation waveform within the quadrature demodulator. In addition, the envelope modulation waveform is derived from the quadrature demodulation local oscillator, thereby establishing the coherent signal required for detection.
The step-FM pulse burst envelope modulation waveform of the present disclosure has been demonstrated to be compatible with MEMS fast scanning mirror.
The achievement of signal processing gain in direct detection LiDAR systems far exceeds the modest increase in hardware complexity. The availability of integrated circuit phase-locked loop and quadrature demodulation functions assures ease of implementation with minimum impact to system volume, operating power and cost. Notably, the LiDAR architecture described herein in detail facilitates systems with lower transmit power, longer measurement range, reduced power consumption and potentially better performance in multiple system deployment conditions. Also, according to exemplary embodiments, due to the increase in signal-to-noise ratio, range measurement error or variance is reduced.
In some other exemplary embodiments, repetition of the data acquisition process to fill additional data matrices can provide simultaneous high resolution range and Doppler measurement.
According to exemplary embodiments, a synthetic Doppler technique is employed for increasing processing gain in radar and LiDAR measurement systems using linear FM ramp, i.e., FMCW, and pulse transmission modulation waveforms, as described above in detail. Frequency ramp deviation ΔF and time duration ΔT are determined for the linear FMCW modulation waveform. Pulse width and pulse repetition frequency are determined for the pulse modulation waveform. According to the disclosure, synthetic Doppler is numerically applied to each waveform for the purpose of increasing the effective processing gain. Two-dimensional FFT and conventional pulse Doppler processing techniques are utilized using a numeric incremental increase in phase, which is indexed to the frequency ramp or pulse repetition frequency in the case of single-beam systems, or antenna scan in the case of multiple beam systems. The synthetic Doppler technique of the present disclosure is particularly effective in the detection of stationary objects, which typically are not suitable for two-dimensional FFT processing.
LiDAR systems, for example, automotive LiDAR systems, have challenging and competing operational objectives. Accurate, high-resolution range measurement requires wide transmission bandwidth, which competes with the cost of wide dynamic range, high-sampling-rate analog-to-digital converters (ADCs). High-resolution azimuth and elevation beam scanning requires narrow beam width and beam position dwell time, which compromise data acquisition and system response time. Range and position measurement accuracy require high signal-to-noise ratio (SNR), which is limited by transmit power and available signal processing gain techniques. The previously described transmit envelope modulation techniques, coupled with quadrature demodulation, have demonstrated improvement of the direct detection LiDAR architecture to address the automotive deployment challenges. However, enhancement of SNR at the signal detection stage offered by two-dimensional (2-D) processing has not been achieved due to limitations of Doppler resolution and detection, even at high relative velocity. To facilitate 2-D signal process and thereby improve detection SNR, the technique described herein employs numeric incremental phase increase to the demodulated signal. In addition, because the technique implements a known “synthetic” Doppler frequency, spectrum resolution analysis requires determination of a single element of the signal spectrum and thereby reduces computation time.
As used herein, the term “synthetic Doppler” refers to incremental phase addition to a signal in a manner analogous to Doppler offset frequency resulting from the change in signal transmission phase engendered by relative-velocity-induced range change. This synthetic Doppler is not utilized to measure relative velocity; however, the technique described herein provides signal processing options similar to those afforded by a true Doppler frequency, e.g., 2-D FFT in the case of FMCW waveforms and pulse Doppler processing in the case of pulsed waveforms, and is applicable to operational scenarios in which true Doppler is restrictive due to stationary or small relative motion, or operational frequencies that restrict Doppler frequency magnitude.
According to exemplary embodiments, the synthetic Doppler of the disclosure can be implemented using a variety of techniques. For example, in a first implementation, a phase modulator can be inserted directly in the local oscillator (LO) path to the quadrature demodulator. In a second implementation, a direct digital synthesizer (DDS), which is utilized for both transmit and receive signals, may be phase modulated during the receive interval, i.e., following the transmit pulse. Alternatively, a second DDS for the LO may be added to implement phase modulation upon successive frequency ramps, while operating from the same clock. In a third implementation, an incremental indexed phase shift may be numerically added to the I-channel and Q-channel signal components following acquisition by the ADC or within the complex FFT (CFFT) signal components for the FMCW waveform.
The synthetic Doppler techniques of the present disclosure, described herein in detail, include FMCW and/or pulsed LiDAR data acquisition and two-dimensional (2-D) fast Fourier transform (FFT) processing. The techniques facilitate 2-D processing for operational scenarios in which Doppler frequency resolution is limited, or to enhance detection of stationary objects via signal processing gain as measure by the increase in signal-to-noise ratio (SNR). It is noted that the technique of the disclosure enables increased signal processing gain without attendant increase to ADC sampling rate. An estimate of signal processing gain for single-dimension processing is 10·log (N). An estimate of signal processing gain for two-dimensional processing is 10·log (n×N).
Each column of the repopulated data matrix of
It should be noted that each column of the second repopulated data matrix of
Referring in particular to
According to the exemplary embodiments, processing gain is realized in accordance with 10×Log (n×N). Data acquisition time is defined as Tacq=n×ΔT. An N-point CFFT is executed for each frequency ramp. Single-frequency spectral analysis is executed for synthetic “Doppler” since the “Doppler” frequency is known. Additional processing gain of 10×Log (n) is realized at the cost of computation of the n-point CFFT and the spectral search execution time.
With regard to antenna beam scanning,
Tacq=n×Tscan=0.064 second.
The foregoing detailed description is related to the synthetic Doppler technique of the exemplary embodiments using the FMCW envelope modulation waveform. As described above, the synthetic Doppler technique of the disclosure can also be carried out using the pulsed envelope modulation waveform. As described below in detail, the implementation of the synthetic Doppler technique using the pulse envelope modulation waveform is more direct and requires only a single complex FFT following data acquisition.
Each column of the original data matrix of
Tacq=n×Tscan=0.0512 second.
As described above, according to exemplary embodiments, the synthetic Doppler of the disclosure can be implemented using a variety of techniques. For example, in another implementation, a phase modulator can be inserted directly in the local oscillator (LO) path to the quadrature demodulator.
Application of the synthetic Doppler technique of the present disclosure described herein in detail provides an advantageous operational feature in an environment including relative motion. The technique enables differentiation of stationary and moving target objects, as well as target objects which are decreasing and increasing in range. Along these lines, according to the present disclosure, the synthetic Doppler incremental phase is added to all range bin columns of the first FFT. Because the synthetic Doppler frequency is known, all the range bins of stationary objects will be located at the known synthetic Doppler frequency. Further, all closing objects will be located in frequency bins above the synthetic Doppler frequency, while objects of increasing range will be located below the synthetic Doppler frequency. The same signal processing gain is available to stationary and moving objects.
The experimental data indicates further opportunities to exploit the signal processing gain. Additional modulation and coding waveforms are considered with system performance objectives of increased processing gain, measurement accuracy and spatial resolution.
It is noted that the present disclosure describes a LiDAR system installed in an automobile. It will be understood that the system of the disclosure is applicable to any kind of vehicle, e.g., bus, train, etc., or the LiDAR system of the present disclosure need not be associated with any kind of vehicle.
It is also noted that the foregoing detailed description is directed primarily to LiDAR detection systems. It will be understood that the present disclosure is also applicable to other forms of detection systems, such as radar systems.
Whereas many alterations and modifications of the disclosure will become apparent to a person of ordinary skill in the art after having read the foregoing description, it is to be understood that the particular embodiments shown and described by way of illustration are in no way intended to be considered limiting. Further, the subject matter has been described with reference to particular embodiments, but variations within the spirit and scope of the disclosure will occur to those skilled in the art. It is noted that the foregoing examples have been provided merely for the purpose of explanation and are in no way to be construed as limiting of the present disclosure.
While the present inventive concept has been particularly shown and described with reference to exemplary embodiments thereof, it will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present inventive concept as defined by the following claims.
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