The present disclosure generally relates to the field of radar sensor systems and devices, and signal processing employed in such systems and devices. In particular, the invention relates to the cancellation of noise caused by undesired radar echoes from short range (SR) targets (also referred to as short-range leakage).
Radar systems are well-known in the art, and can generally be divided into pulse radar systems and continuous-wave (CW) systems. A pulse radar system measures a distance to an object (usually referred to as target) by transmitting a short radio-frequency (RF) pulse to an object, and measuring the time taken for the reflected pulse (i.e. the echo) to be received. As the velocity of the pulse is known (i.e. the speed of light), it is straightforward to calculate the distance to an object. However, pulse radar systems are not suitable for use measuring distances of a few 100 meters, in particular because the pulse length must be reduced as the travel time (i.e. distance to the target) decreases. As the pulse length decreases, the energy contained within the pulse decreases, to the point where it becomes impossible to detect the reflected signal. Instead, continuous-wave radar systems are used for measuring comparably short distances. In many applications, such as in automotive applications, so-called frequency modulated continuous-wave (FMCW) radar systems are used to detect targets in front of the radar device and measure the distance to the target as well as their velocity.
Different from pulsed radar systems, in which isolation between the transmit signal path and the receive signal path is not specifically relevant due to the pulsed operation of the transmitter, a phenomenon referred to as leakage is an issue in FMCW radar systems. Leakage generally describes the problem that a small fraction of the frequency-modulated transmit signal “leaks” into the receive signal path of the radar transceiver without being back-scattered by a target. If the cause of the leakage is in the RF frontend of the radar transceiver (i.e. imperfect isolation of the circulator, which separates receive signal and transmit signal in a monostatic radar configuration) leakage is also referred to as crosstalk between the transmit signal path and the receive signal path. When integrating the radar system in one single monolithic microwave integrated circuit (MMIC) crosstalk or so-called on-chip leakage is always an issue.
Another cause of leakage may be objects, which are very close to the radar antenna (such as, e.g., a fixture or a cover mounted a few centimeters in front of the radar antennas). Herein, reflections of the transmitted radar signal at such objects are referred to as short-range leakage, which is a fraction of the transmit signal emanating from the transmit antenna and reflected back (back-scattered) to the receive antenna of the FMCW radar system at the mentioned objects, which are very close to the radar antenna(s). It shall be understood that the transmit antenna and the receive antenna are physically the same antenna in monostatic radar systems. Herein, the mentioned reflections caused by short-range targets are referred to as short-range leakage as their effect is similar to the effect of on-chip leakage. However, known methods, which are suitable for the cancellation of on-chip leakage or cross-talk are not suitable for the cancellation of short-range leakage.
In radar systems the overall noise floor limits the sensitivity, with which radar targets can be detected, and thus also limits the accuracy of the distance measurement. Generally, this noise floor is dominated by the additive noise of the transmission channel. However, in case a short-range target reflects the transmitted radar signal with comparably high amplitude (i.e. causes short-range leakage) the phase noise (PN) of the transmitted radar signal may dominate the noise floor. The phase noise results in a deteriorated signal detection quality or even makes the detection of radar targets with small radar cross sections impossible.
Exemplary embodiments disclosed herein relate to a radar device. In accordance with one example of the present invention the radar device includes an RF transceiver configured to transmit an RF oscillator signal to a radar channel and receive a respective first RF radar signal from the radar channel. The radar device further includes an artificial radar target composed of circuitry that provides a gain and a delay to the RF oscillator signal to generate a second RF radar signal. A first frequency conversion circuit, which includes a first mixer, is configured to down-convert the first RF radar signal, and a second frequency conversion circuit, which includes a second mixer, is configured to down-convert the second RF radar signal. An analog-to digital conversion unit is configured to digitize the down-converted first RF radar signal and the down-converted second RF radar signal to generate a first digital signal and a second digital signal, respectively. A digital signal processing unit receives the first and second digital signals and is configured to estimate a phase noise signal included in the second digital signal and to generate a cancellation signal based on the estimated phase noise signal. The cancellation signal is subtracted from the first digital radar signal to obtain a noise compensated digital radar signal.
Other exemplary embodiments of the present invention relate to a method for cancelling noise in a radar signal. In accordance with one example of the invention the method includes transmitting an RF oscillator signal to a radar channel and receive a respective first RF radar signal from the radar channel, and applying the RF oscillator signal to an artificial radar target composed of circuitry, which applies a delay and a gain to the RF oscillator signal, to generate a second RF radar signal. The first RF radar signal and the second RF radar signal are down-converted from a RF frequency band to a base band, and the down-converted first RF radar signal and the down-converted second RF radar signal are digitized to generate a first digital signal and a second digital signal, respectively. Moreover, the method includes estimating a phase noise signal included in the second digital signal, and generating a cancellation signal based on the estimated phase noise signal. The cancellation signal is subtracted from the first digital radar signal to obtain a noise compensated digital radar signal.
The invention can be better understood with reference to the following drawings and descriptions. The components in the figures are not necessarily to scale; in-stead emphasis is placed upon illustrating the principles of the invention. More-over, in the figures, like reference numerals designate corresponding parts. In the drawings:
The radar device 100 may include or be implemented in a monolithic microwave integrated circuit (MMIC), which includes circuitry for providing the core functions needed for distance and/or velocity measurement in one chip (also referred to as “single chip radar”). Thus the chip may include, inter alia, RF oscillators, amplifiers, mixers, filters, analog-to-digital converters, and digital signal processors.
As mentioned, the mixer 110 down-converts the radar signal (amplified antenna signal A·yRF(t), amplification factor A) into the base band. The respective base band signal (mixer output signal) is denoted by y(t). The base band signal y(t) is then subject to analog filtering (filter 115) to suppress undesired sidebands or image frequencies, which may be a result of the mixing operation. The filter 115 may be a low-pass filter or a band-pass filter. The filtered base band signal (filter output signal) is denoted by y′(t). Receivers (or the receiver portions of transceivers) which make use of a mixer to down-convert the received RF signal into the base band are as such known as heterodyne receivers and thus not further discussed in more detail. The filtered base band signal y′(t) is then sampled (temporal discretization) and converted to a digital signal y[n] (analog-to-digital converter (ADC) 120), which is then further processed in the digital domain using digital signal processing (n being the time index). The digital signal processing may be performed in a digital signal processing unit 125, which may include, e.g., a digital signal processor (DSP) executing appropriate software instructions.
The transmission channel 200 represents the signal path from the transmit antenna 101 to the target and back to the receive antenna 102. While passing through the transmission channel the radar signals sRF(t) (transmitted signal) and yRF(t) (back-scattered signal) are subject to additive noise w(t), which is usually modelled as additive white Gaussian noise (AWGN).
sRF(t)=cos(2πf0t+πkt2+φ(t)+Φ), (1)
wherein f0 is the start frequency of the chirp signal, k (k=B/T) denotes the slope of the chirp with bandwidth B and duration T, Φ is a constant phase offset and φ(t) is the introduced phase noise (PN) due to imperfections of the local oscillator (see
The transmission channel 200 (see
yRF(T)=AS·sRF(t−τS)+Σi=1N
wherein the first summand represents the signal component due to the short-range leakage, the second summand represents the signal components due to reflections at the “normal” radar target(s) and the last summand represents AWGN. The delays τS and τTi are also referred to as round trip delay times (RTDT) associated with the short-range target and the targets Ti, respectively. It should be noted that, in the present disclosure, the previously mentioned on-chip leakage is not considered as several concepts for cancelling on-chip leakage exist.
As can be seen from
The beat frequencies resulting from the short-range leakage and the reflections at the normal targets are denoted as fBS and fBT
fBS=kτS, and fBT
Furthermore, the constant phase ΦS and ΦT
ΦS=2πf0τS+kπτS2, and ΦT
The beat frequencies (equations 4) and constant phases (equations 5) depend only on given system parameters (such as the start frequency f0 of the chirp as well as its bandwidth and duration as represented by the variable k=B/T) and the RTDTs τS and τTi associated with the short-range leakage and the radar targets Ti to be detected, respectively. It follows from equations 3, 4 and 5 that the signal component of y′(t), which results from the short-range leakage (i.e. the first summand in equation 3), is zero when the RTDT τS is zero (τS=0). Even the term φ(t)−φ(t−τS) becomes zero when the delay time τS is zero. With increasing values of the RTDT τS (i.e. with increasing distance of the short-range target) the correlation of the phase noise components φ(t) and φ(t−τS) decreases. This effect is called range correlation effect and the phase difference φ(t)−φ(t−τS) is referred to as decorrelated phase noise DPN. It is noted that DPN is usually not an issue in the context of on-chip leakage as the associated delay is negligibly small.
In the following, the first summand of equation 3, i.e. the short-range leakage signal
is analyzed in more detail (see
SΔφ(f)=Sφ(f)·2(1−cos(2πτSf)), (7)
wherein Sv(f) is the power spectrum of the phase noise signal φ(t) included in the RF transmit signal sRF(t). Further analysis of a realistic example (τS=800 ps, dS≈12 cm) shows that, for frequencies higher than 100 kHz, the noise level of the DPN is −140 dBm, assuming a transmit power of 10 dBm and an AWGN noise floor of −140 dBm. The presence of DPN entails an increase of the noise floor and results in a 10 dB reduction of sensitivity for the detection of radar targets. As a result, the total noise floor increases, which is equivalent to a loss of sensitivity of 10 dB for the detection of radar targets.
To at least reduce the effect of the DPN due to (unavoidable) short-range targets an (artificial) on-chip target (OCT) is included in the radar device and incorporated in the signal processing chain as illustrated in
Theoretically, it would be desirable that the delay τO of OCT 300 equals the RTDT τS of the short-range target present in radar channel 200. In realistic examples the RTDT τS of the short-range target is in the range of a few hundreds of picoseconds up to a few nanoseconds, whereas the delay τO of an on-chip target is practically limited to a few picoseconds when implementing the radar device on a single MMIC. In a single-chip radar higher values of delay τO (which would be needed in case of τO=τS) would result in an undesired (or even unrealistic) increase in chip area and power consumption and are thus only economically feasible when using discrete circuit components. Therefore, the delay τO of OCT 300 is limited to values that are significantly lower than the RTDT τS of any practically relevant short-range target.
Further analysis of the properties of the cross-correlation coefficient of the decorrelated phase noise (DPN) signals
ΔφS(t)=φ(t)−φ(t−τS), (8)
i.e. the DPN included in the RF signal received from the short-range target TS (see
ΔφO(T)=φ(t)−φ(t−τO) (9)
i.e. the DPN included in the RF signal received from OCT 300, shows that the cross-correlation coefficient
is very similar for different values of OCT delay τO (the operator E denoting the expected value and τΔφ
As the DPN φO(t) included in the down-converted RF signal
received from OCT 300 and the DPN φS(t) included in the baseband signal yS(t) received from the short-range target (see equation 6) are highly correlated, the DPN included in the baseband signal yO(t) obtained from OCT 300 can be used to estimate the DPN caused by the short-range leakage. In equation 11 fBO denotes the beat frequency caused by OCT 300 and is calculated analogously to fBS (see equation 4). Also the constant phase ΦO is computed in an analogous manner as constant phase ΦS (see equations 5 and 14). In a practical example the RTDT τS associated with the short-range target TS is approximately 800 ps (corresponds to dS=12 cm), whereas the OCT delay time τO is only 40 ps. Therewith, the beat frequency fBS is 20 times higher than beat frequency fBO.
As can be seen from
Using the mentioned sampling time offset for maximization of the correlation coefficient results in a high correlation coefficient ρΔφ
As the DPN signals included in the discrete time signals y[n] and yO[n] (provided by analog-to-digital converters 120 and 120′, respectively) are highly correlated (particularly when using the mentioned sampling time offset), an estimation of the discrete-time DPN signal ΔφO[n] may be calculated from the down-converted signal yO[n] obtained from OCT 300. This estimation and the subsequent calculation of a corresponding cancellation signal is performed by the function block 130 labelled LC (leakage cancellation). Therefore, the LC function block basically provides the two functions of estimating the DPN from signal yO[n] and generating a cancellation signal ŷS[n] to be subtracted from the down-converted and digitized radar signal y[n] in order to eliminate the short-range leakage (see also equation 6) included in the radar signal y[n].
The discrete-time version of equation 11 is
wherein fS is the sampling rate determined by the period TA of the sampling clock signal (fA=TA−1). Applying the trigonometric identity
cos(a+b)=cos(a)cos(b)+sin(a)sin(b) (15)
and the approximations (since ΔφO [n] is sufficiently small)
cos(ΔφO[n])≈1 and (16)
sin(ΔφO[n])≈ΔφO[n] (17)
to equation 13 simplifies it to
As the gain AO and the beat frequency fB0 are a-priori known system parameters of the radar system the DPN ΔφO[n] can be approximated based on the down-converted signal yO[n], which is received from the OCT, in accordance with the following equation:
Beat frequency fBO and phase ΦO may be measured after production of the radar device as a part of a system test and calibration procedure. These parameters can be computed in the same manner as for the short-range leakage signal yS[n] (see equations 4 and 5 and equation 14). In order to account for parameter variations of OCT 300 (e.g. due to temperature changes) beat frequency fBO and phase ΦO may be estimated repeatedly and updated regularly.
In an alternative embodiment, the DPN may be obtained by applying a high-pass filter to the signals yO[n] as the phase noise is dominant in the range of a few hundred kHz. In essence, the high-pass filter can eliminate the first summand in equation 18.
As the DPN signals ΔφO[n] and ΔφS[n] are highly correlated, the short-range leakage signal (cf. equation 6)
can be approximated as
where α is referred to as DPN gain. Gain α can be determined with the help of the auto-covariance function
cΔφ
and the cross-covariance function
cΔφ
The DPN gain α can then be determined as
Note that the numerator equals equation 23 (resulting in α=1) when τO=τS (see also
The estimated short-range leakage signal ŷS[n] is generated by the LC function block 130 illustrated in
z[n]=y[n]−ŷS[n]. (25)
The cancellation method is summarized in the flow-chart of
Although the invention has been illustrated and described with respect to one or more implementations, alterations and/or modifications may be made to the illustrated examples without departing from the spirit and scope of the appended claims. In particular regard to the various functions performed by the above described components or structures (units, assemblies, devices, circuits, systems, etc.), the terms (including a reference to a “means”) used to describe such components are intended to correspond unless otherwise indicated to any component or structure, which performs the specified function of the described component (e.g., that is functionally equivalent), even though not structurally equivalent to the disclosed structure, which performs the function in the herein illustrated exemplary implementations of the invention.
In addition, while a particular feature of the invention may have been disclosed with respect to only one of several implementations, such feature may be combined with one or more other features of the other implementations as may be desired and advantageous for any given or particular application. Furthermore, to the extent that the terms “including”, “includes”, “having”, “has”, “with”, or variants thereof are used in either the detailed description and the claims, such terms are intended to be inclusive in a manner similar to the term “comprising”.
Number | Date | Country | Kind |
---|---|---|---|
10 2015 100 804 | Jan 2015 | DE | national |
Number | Name | Date | Kind |
---|---|---|---|
3128462 | Woolfson | Apr 1964 | A |
5055850 | Lamper | Oct 1991 | A |
5138325 | Koury | Aug 1992 | A |
5189427 | Stove | Feb 1993 | A |
5828333 | Richardson | Oct 1998 | A |
6054948 | Dean | Apr 2000 | A |
6067861 | Shekarriz | May 2000 | A |
7075378 | Howe | Jul 2006 | B2 |
8258877 | Goel | Sep 2012 | B2 |
8718115 | Dabak | May 2014 | B2 |
20040006436 | Morgen | Jan 2004 | A1 |
20060203324 | Harris | Sep 2006 | A1 |
20080062405 | Hill | Mar 2008 | A1 |
20080088503 | Beasley | Apr 2008 | A1 |
20090322578 | Petrovic | Dec 2009 | A1 |
20100265121 | Bandhauer | Oct 2010 | A1 |
20110102246 | Moulton | May 2011 | A1 |
20120092205 | Bourdelais | Apr 2012 | A1 |
20150378017 | Ferguson | Dec 2015 | A1 |
Number | Date | Country |
---|---|---|
2001141811 | May 2001 | JP |
20120116335 | Oct 2012 | KR |
Number | Date | Country | |
---|---|---|---|
20170199270 A1 | Jul 2017 | US |