JP7399706B2 - Radar device and its radar signal processing method - Google Patents

Description

The present embodiment relates to a radar device and its radar signal processing method.

With conventional radar equipment, when detecting low-speed moving targets such as drones in a cluttered environment, the Doppler component is small, so it was necessary to suppress the effects of clutter and nearby reflected waves with similar Doppler components. . MTI (non-patent document 5) is a method for suppressing clutter, but when suppressing clutter using this method, there is a problem in that even the target component is suppressed.

Japanese Patent Application Publication No. 2014-182010

FMCW method (up chirp and down chirp), Yoshida, 'Revised radar technology', Institute of Electronics, Information and Communication Engineers, pp.274-275 (1996) Phase Monopulse, Yoshida, ‘Revised Radar Technology’, Institute of Electronics, Information and Communication Engineers, pp.260-264 (1996) CFAR (CA-CFAR, GO-CFAR), Sekine, 'Radar signal processing technology', Institute of Electronics, Information and Communication Engineers, pp.96-103 (1991) 2D CFAR, Guy Morris, Airborne Pulsed Doppler Radar 2nd edition, Artech House, pp.399-417(1996) MTI, Yoshida, ‘Revised Radar Technology’, Institute of Electronics, Information and Communication Engineers, pp.66-77 (1996)

As described above, in conventional radar devices, when detecting a low-speed target, there is a problem in that when suppressing the effects of clutter and close reflected waves, even the target component is suppressed.

The present embodiment has been developed in view of the above-mentioned problems, and aims to provide a radar device and its radar signal processing method that can accurately detect a low-speed target while suppressing the effects of clutter and nearby reflected waves. .

In order to solve the above problem, the radar device according to the present embodiment uses, as a first means, a transmission pulse whose number of hits is N (N≧1) transmitted from the transmission system in one scanning period in the range direction. A CPI (Coherent Pulse Interval) signal corresponding to each reception period of the N hit transmission pulses is extracted from the received signal obtained by receiving the reflected signal in the receiving system, and the slow-time for each range cell is extracted from the CPI signal. Extract the complex signal of the slow-time axis, calculate an m (m ≧ 1) order approximate curve of the complex signal of the slow-time axis, and subtract the complex signal of the approximate curve from the original complex signal of the slow-time axis. The slow-time axis complex signal with the suppressed low frequency component is converted into a frequency domain signal, and the slow-time axis complex signal converted to the frequency domain is calculated for each range cell. GO (Greatest Of)-CFAR (Constant False Alarm Rate), which divides the test cell by the maximum amplitude of the reference cells on both sides of the test cell within a predetermined frequency cell width, centering on 0 Doppler on the Doppler frequency axis. Otherwise, select CA (Cell-Averaging)-CFAR that divides the test cell by the amplitude average of the reference cells on both sides of the test cell, and perform each CFAR process to achieve the target. Detects the range-Doppler cell in which the range-Doppler cell exists, performs ranging and angle measurement processing on the detected range-Doppler cell, and outputs it as target information .

In addition, as a second means, the received signal obtained by receiving the reflected signal of the transmission pulse that is transmitted from the transmission system in one scanning period in the range direction with N (N≧1) hits in the reception system is used. Extract a CPI (Coherent Pulse Interval) signal corresponding to each reception period of N hits of transmitted pulses, extract a slow-time axis complex signal for each range cell from the CPI signal, and extract the slow-time axis complex signal from the CPI signal. An m (m ≧ 1) approximation curve is calculated, and the complex signal of the approximation curve is subtracted from the original slow-time axis complex signal to suppress the low frequency component, and the low frequency component is suppressed. The complex signal on the slow -time axis is converted to a signal in the frequency domain, and the complex signal on the slow-time axis converted to the frequency domain is divided into a range around the test cell, centering on 0 Doppler on the Doppler frequency axis for each range cell. - A two-dimensional CFAR (Constant False Alarm Rate) process that provides a two-dimensional reference cell on the Doppler frequency axis and divides the test cell using the average amplitude value or maximum amplitude value of the reference cell. The range-Doppler cell in which the target exists is detected, and the detected range-Doppler cell is subjected to ranging and angle measurement processing and output as target information.

In addition, as a third means, the receiving system receives the reflected signal of the transmitting signal that is transmitted from the transmitting system during one scanning period in the range direction and whose frequency modulation is a continuous N (N≧1) sweep, thereby modulating the frequency at the time of transmission. A CPI (Coherent Pulse Interval) signal corresponding to each reception interval of the real N sweep transmission signal is extracted from the beat frequency received signal mixed with a local frequency signal adjusted to the slow-time Extract the fast-time axis real number signal for each sweep number on the axis, calculate the m (m ≥ 1) order approximation curve of the fast-time axis real number signal, and convert the real number signal of the approximation curve to the original fast - Suppress low frequency components by subtracting from the real signal on the time axis, convert the real signal on the fast-time axis with the low frequency components suppressed into a signal in the frequency domain of complex numbers, and convert the fast signal converted to the frequency domain. The complex signal on the -time axis is converted to a complex signal by setting the positive or negative frequency components to 0, and then subjected to CFAR (Constant False Alarm Rate) processing to generate the fast-time axis where the target exists. A cell is detected, and the detected fast-time axis cell is subjected to distance measurement/velocity measurement processing and angle measurement processing, and is output as target information .

FIG. 2 is a block diagram showing the configuration of a transmission system and a reception system of the radar device according to the first embodiment. FIG. 4 is a timing waveform diagram showing transmission signals generated in a transmission system in the first embodiment. FIG. 4 is a timing diagram showing a CPI signal based on the PRI of a received signal in the first embodiment. FIG. 3 is a waveform diagram showing amplitude changes of slow-time axis received signals for each range cell in the first embodiment. 2 is a range-Doppler diagram showing a comparison of signals after slow-time axis FFT before and after low-frequency component suppression in the first embodiment; FIG. FIG. 2 is a block diagram showing the configuration of a transmission system and a reception system of a radar device according to a second embodiment. FIG. 7 is a timing waveform diagram showing a continuous sweep transmission modulation signal generated in a transmission system and a beat detection signal obtained in a reception system in the second embodiment. FIG. 7 is a timing diagram showing a CPI signal of a received signal with respect to a sweep transmission signal in the second embodiment. FIG. 7 is a waveform diagram showing amplitude changes of fast-time axis received signals for each slow-time axis sweep number obtained in the receiving system in the second embodiment. FIG. 7 is a block diagram showing the configuration of a transmission system and a reception system of a radar device according to a third embodiment. FIG. 7 is a waveform diagram showing how a complex number signal is generated from a signal subjected to fast-time axis FFT of a real number in a receiving system in the third embodiment. An angle-amplitude waveform diagram and an angle-error voltage waveform diagram showing angle measurement processing using a phase monopulse in the third embodiment. FIG. 7 is a block diagram showing the configuration of a transmission system and a reception system of a radar device according to a fourth embodiment. The range-Doppler diagram showing the range of GO-CFAR and the range of CA-CFAR set around 0 Doppler in the fourth embodiment. FIG. 7 is a block diagram showing a CA-CFAR method and a GO-CFAR method in the fourth embodiment. FIG. 10 is a waveform chart that compares and shows the state of processing near a null edge in CA-CFAR and GO-CFAR in the fourth embodiment. FIG. 7 is a block diagram showing the configuration of a transmission system and a reception system of a radar device according to a fifth embodiment. FIG. 10 is a range-Doppler diagram showing the processing when two-dimensional CFAR of the range-Doppler axis is applied in the fifth embodiment.

Embodiments will be described below with reference to the drawings. In the description of each embodiment, the same parts are denoted by the same reference numerals, and redundant description will be omitted.

(First embodiment)
A radar device according to a first embodiment will be described with reference to FIGS. 1 to 5.
1 to 5 show the configuration and processing example of a radar device according to the first embodiment, FIG. 1 is a block diagram showing the configuration of a transmission system and a reception system, and FIG. 2 is a transmission system generated by the transmission system. Figure 3 is a timing diagram showing CPI data based on PRI of the received signal. Figure 4 is a waveform diagram showing amplitude changes of the received signal on the slow-time axis for each range cell. Figure 5 is low frequency component suppression. It is a range-Doppler diagram showing a comparison of signals after slow-time axis FFT before and after.

First, in FIG. 1, in the transmission system, a transmission signal generator 11 generates a transmission signal (FIG. 2) such as a modulated pulse, a DA converter 12 converts it into an analog signal, and a frequency converter 13 converts it into a radio frequency (RF) signal. The signal is converted into a signal, power amplified by a high-output amplifier 14, and transmitted by an antenna 16 via a circulator 15. In the receiving system, a reflected signal from a target etc. is captured by an antenna 16, sent and received by a circulator 15, and after being amplified by reducing noise by a low noise amplifier 17, the frequency is converted to baseband by a frequency converter 18. , is converted into a digital signal by an AD converter 19.

The above transmission/reception signal is called a CPI (Coherent Pulse Interval) signal based on a reception signal (PRI signal, PRI: Pulse Repetition Interval) of N (N≧1) hit transmission pulses. Hereafter, target detection processing is performed. First, the CPI signal input unit 21 inputs the received signal (PRI signal) of the N (N≧1) hit transmission pulse output from the AD converter 19 and extracts the CPI signal from the received signal. The slow-time signal extraction unit 22 extracts a slow-time axis signal (complex signal) for each range cell from the CPI signal. The approximate curve calculation unit 23 calculates an approximate curve of the extracted slow-time axis signal. The approximate curve subtraction unit 24 suppresses low frequency components by subtracting the calculated approximate curve signal from the original signal. The slow-time FFT processing unit 25 performs FFT (Fast Fourier Transform) processing on the slow-time axis signal to convert it into a frequency domain signal. The CFAR processing unit 26 performs CFAR (Constant False Alarm Rate) processing on the Doppler frequency axis for each range cell on the slow-time axis signal converted to the frequency domain, and calculates the range-Doppler cell where the target exists. Detect. The distance measurement/angle measurement processing section 27 subjects the detected range-Doppler cell to distance measurement/angle measurement processing and outputs it as target information.

In the above configuration, target detection processing of the first embodiment will be described.

As shown in FIG. 3, the CPI signal is two-dimensional data of a fast-time axis for each range cell and a slow-time axis between PRIs. The slow-time axis received signal for each range cell is a complex signal with amplitude changes as shown in FIG. Furthermore, the slow-time axis received signal for each range cell includes a target signal and clutter. Among these, clutter, especially ground clutter in fixed ground radar, is a low frequency component near Doppler 0. On the other hand, unless the target is a fixed target, the target signal has a Doppler component due to velocity. Therefore, consider separating the clutter and the target signal.

First, the slow-time axis received signal (complex signal) for each range cell is extracted from the CPI signal (21) (22), and as shown in Figure 4, a low-order (m (m≧1) order) approximation is performed. Calculate the curve (23). For this approximate curve, the coefficients may be determined by the method of least squares or the like using, for example, the polynomial approximation formula shown in equation (1).

この際、次数mを大きくすると、クラッタ成分以上の目標信号まで近似するため、想定する目標信号まで抑圧しないように、低次の次数（例えば１～３程度）に設定する必要がある。ここで算出した近似式の信号を元の受信信号から減算することにより、低周波成分を抑圧する（２４）。これを全レンジセル毎（fast-time軸セル）に繰り返し、slow-time軸でFFT処理して（２５）、レンジセル毎にドップラ周波数軸でCFAR処理を行うことによりレンジ－ドップラセルの目標検出処理を行う（２６）。目標を検出したレンジ－ドップラセルについては、測距・測角処理して、目標情報として出力する（２７）。

At this time, if the order m is increased, it approximates a target signal that is higher than the clutter component, so it is necessary to set it to a low order (for example, about 1 to 3) so as not to suppress the expected target signal. By subtracting the signal of the approximate expression calculated here from the original received signal, low frequency components are suppressed (24). Repeat this for every range cell (fast-time axis cell), perform FFT processing on the slow-time axis (25), and perform CFAR processing on the Doppler frequency axis for each range cell to perform range-Doppler cell target detection processing. (26). The range-Doppler cell that detected the target undergoes distance measurement and angle measurement processing and is output as target information (27).

FIG. 5 shows how the clutter components are suppressed. FIG. 5(a) shows a signal after slow-time axis FFT processing before low frequency component suppression, and FIG. 5(b) shows a signal after slow-time axis FFT processing after low frequency component suppression. Before suppressing clutter using the range-Doppler axis, as shown in Figure 5(a), the low-speed target component near the clutter cannot be separated from the clutter component due to the spread of the clutter component, and the low-speed target component near the clutter cannot be separated from the low-speed target component near the clutter. cannot be detected. On the other hand, when the signal of the approximate curve shown in FIG. 4 is subtracted to suppress clutter on the range-Doppler axis, a sharp null is formed in the clutter component as shown in FIG. 5(b). This makes it possible to separate the low-speed target component near the clutter from the clutter component, and it is possible to suppress only the clutter and detect the low-speed target component.

Therefore, the radar device according to the above embodiment calculates an m-th (m≧1) approximation curve from a complex signal on the slow-time axis for each cell on the fast-time axis. By subtracting it from the original signal, low frequency signal components (clutter, close reflected waves, etc.) are suppressed and target detection processing (pulse compression, CFAR, etc.) is performed. It is possible to detect only low-speed targets by suppressing clutter and proximity reflection signals while maintaining the

(Second embodiment)
A radar device according to a second embodiment will be described with reference to FIGS. 6 to 9.
In the first embodiment, a method was described in which an approximate curve is subtracted from a slow-time axis signal for each cell on a fast-time axis with respect to a CPI signal of a pulse radar. In the case of a pulse radar, normally the signal is not received while transmitting, but in the case of a continuous wave radar, the signal is received while transmitting, so a wrap-around component from the transmission to the circulator to the reception is input. This is called proximity reflection. In this embodiment, a method for suppressing a proximity reflected signal will be described in the case of a continuous wave radar such as an FMCW radar.

6 to 9 show the configuration and processing examples of the radar device according to the second embodiment, FIG. 6 is a block diagram showing the configuration of the transmission system and the reception system, and FIG. 7 is a block diagram showing the configuration of the transmission system and the reception system. Timing waveform diagram showing the sweep transmit modulation signal and beat detection signal obtained in the receiving system. Figure 8 is a timing diagram showing the CPI signal of the received signal for the sweep transmit signal. Figure 9 is the slow-time axis sweep obtained in the receiving system. FIG. 7 is a waveform diagram showing the amplitude change of the fast-time axis received signal for each number. Note that in FIG. 6, the same parts as in FIG. 1 are denoted by the same reference numerals.

In FIG. 6, in the transmission system, the transmission signal generator 11a generates up-sweep 1 and down-sweep 2 signals shown in FIG. 7(a) as continuous sweep transmission signals (transmission modulation signals), 12 into an analog signal, a frequency converter 13 into a radio frequency (RF) signal, a high output amplifier 14 to power amplify the signal, and a circulator 15 to transmit the signal through an antenna 16. In the receiving system, a reflected signal from a target etc. is captured by an antenna 16, sent and received by a circulator 15, and after being amplified by reducing noise by a low noise amplifier 17, the frequency is converted to baseband by a frequency converter 18a. . Here, in the frequency converter 18a, similarly to the transmission modulation signal, the swept local frequency is used to extract the beat frequency that is the difference from the received signal shown in FIG. 7(b) (see Non-Patent Document 1 ). In the receiving system, an AD converter 19 converts the beat frequency received signal output from the frequency converter 18a into a digital signal.

Through the above transmission and reception processing, N (N≧1) sweep (in the case of N=2 in FIG. 7) received signals (FIG. 8) are obtained. Hereafter, target detection processing is performed. First, the CPI signal input unit 31 extracts a CPI signal from the received signal of the beat frequency based on the N (N≧1) sweep transmission signal from the output of the AD converter 19. The fast-time signal extraction unit 32 extracts a fast-time axis signal (complex signal) for each sweep number on the slow-time axis from the CPI signal. The approximate curve calculation unit 33 calculates an approximate curve of the extracted fast-time axis signal. The approximate curve subtraction unit 34 suppresses low frequency components by subtracting the calculated approximate curve signal from the original signal. The fast-time FFT processing unit 35 performs FFT processing on the fast-time axis signal and converts it into a frequency domain signal. The CFAR processing unit 36 performs CFAR detection processing on the fast-time axis signal converted into the frequency domain to detect cells on the fast-time axis and slow-time axis where the target exists. The ranging/velocity/angle measurement processing section 37 subjects the detected fast-time axis and slow-time axis cells to ranging/velocity measurement processing and angle measurement processing, and outputs them as target information.

In the above configuration, target detection processing according to the second embodiment will be described.

In the above received data, the fast-time axis received signals for each slow-time axis (sweep) number are shown in FIG. This signal includes a close reflection component. The close reflection component is a low frequency component near 0 Doppler. On the other hand, unless the target is a fixed target, the target signal has a Doppler component due to velocity. Here, consider separating the proximity reflection and the target signal.

First, the fast-time axis received signal (complex signal) for each sweep is extracted (32), and a low-order (m (m≧1) order) approximate curve is calculated as shown in Figure 9 (33). ). For this approximate curve, the coefficients may be determined by the method of least squares or the like using, for example, the polynomial approximation formula shown in equation (2).

この際、次数mを大きくすると、近接周波数成分以上の目標信号まで近似するため、想定する目標信号まで抑圧しないように、低次の次数（例えば１～３程度）に設定する必要がある。ここで算出した近似式の信号を元の信号から減算することにより、低周波成分の近接反射信号を抑圧する（３４）。これを全スイープ毎に繰り返す。この信号をfast-time軸でFFT処理して（３５）、CFARによりfast-time軸とslow-time軸のセルの目標検出処理を行う（３６）。検出したfast-time軸とslow-time軸のセルについては、FMCWの測距／測速処理と測角処理を行い（３７）、目標情報として出力する。

At this time, if the order m is increased, the target signal of adjacent frequency components or higher will be approximated, so it is necessary to set it to a low order (for example, about 1 to 3) so as not to suppress the expected target signal. By subtracting the signal of the approximate expression calculated here from the original signal, the proximity reflection signal of the low frequency component is suppressed (34). Repeat this for every sweep. This signal is subjected to FFT processing on the fast-time axis (35), and target detection processing for cells on the fast-time axis and slow-time axis is performed using CFAR (36). The detected fast-time axis and slow-time axis cells are subjected to FMCW distance measurement/velocity measurement processing and angle measurement processing (37), and output as target information.

The distance and speed of the distance measurement/velocity measurement/angle measurement processing section 37 can be calculated by the following equation (see Non-Patent Document 1).

上記の処理により、本実施形態に係るレーダ装置は、FMCWレーダ等の連続波レーダの場合について、fast-time軸の複素信号の低次の近似曲線を用いて近接反射信号を抑圧し、近接反射信号近くの低速目標成分を分離することが可能となり、近接反射信号のみを抑圧して低速目標成分を検出することができる。

Through the above processing, the radar device according to the present embodiment suppresses the proximity reflected signal using a low-order approximation curve of the complex signal on the fast-time axis in the case of continuous wave radar such as FMCW radar, and suppresses the proximity reflected signal. It becomes possible to separate the low-speed target component near the signal, and it is possible to detect the low-speed target component by suppressing only the nearby reflected signal.

(Third embodiment)
A radar device according to a third embodiment will be described with reference to FIGS. 10 to 12.
In the second embodiment, a method for suppressing proximity reflections in the case of continuous wave radar has been described. This received signal is assumed to undergo orthogonal detection in the frequency converter, and the signal after AD conversion is a complex signal (real part + imaginary part signal). On the other hand, in order to simplify the frequency converter, quadrature detection may not be performed, and in that case, the received signal is only a real number signal (real part). In this embodiment, a method will be described in which frequency conversion is performed using only real signals.

10 to 12 show the configuration and processing example of the radar device according to the third embodiment. FIG. 10 is a block diagram showing the configuration of the transmission system and the reception system, and FIG. FIG. 12 is a waveform diagram showing how a complex number signal is generated from a time-axis FFT signal. FIG. 12 is an angle-amplitude waveform diagram and an angle-error voltage waveform diagram showing angle measurement processing using a phase monopulse.

In FIG. 10, after the up-sweep signal and the down-sweep signal are generated by the transmission signal generator 11a, the steps up to the low-noise amplifier 17 are the same as in the second embodiment. In this embodiment, the frequency converter 18b that directly detects the local signal is used instead of using the orthogonal detection (distributing the local signal into orthogonal signals and detecting each one) of the frequency converter 18 used in the second embodiment. The AD converter 19a converts the output into a digital signal to obtain received data as a real number signal. For this received data, if the complex signal in the second embodiment is replaced with a real signal, an approximate curve can be calculated by the same calculation as in the second embodiment. That is, the CPI signal input unit 31a extracts the CPI signal (real number) from the received signal (real number) of the beat frequency based on the N (N≧1) sweep transmission signal of the AD converter 19a. The fast-time signal extraction unit 32a extracts a fast-time axis signal (real number) for each sweep number on the slow-time axis from the CPI signal (real number). The approximate curve calculation unit 33a calculates an approximate curve of the extracted fast-time axis signal (real number). The approximate curve subtraction unit 34a suppresses low frequency components by subtracting the calculated approximate curve signal (real number) from the original signal (real number). The fast-time FFT processing unit 35a performs FFT processing on the fast-time axis signal and converts it into a frequency domain signal (complex number). Here, the frequency processing section 38 sets negative or positive frequency components to 0. The CFAR processing unit 36a performs CFAR detection processing on the fast-time axis signal (complex number) with limited frequency components to detect the fast-time axis cell in which the target exists. The distance measurement/speed measurement/angle measurement processing section 37 subjects the detected fast-time axis cells to distance measurement/speed measurement processing and angle measurement processing, and outputs them as target information.

In the above configuration, target detection processing according to the third embodiment will be described.

First, the CPI signal input unit 31 extracts a fast-time axis signal (real number signal) for each sweep from the received data (32a), and calculates a low-order approximate curve as shown in FIG. 11(a). For this approximate curve, coefficients may be determined by the method of least squares or the like using, for example, a polynomial approximation expression shown in the following equation.

この際、次数mを大きくすると、近接周波数成分以上の目標信号まで近似するため、想定する目標信号まで抑圧しないように、低次の次数（例えば１～３程度）に設定する必要がある。ここで算出した近似式を元の信号から減算することにより、低周波成分を抑圧する（３４ａ）。これを全スイープ毎に繰り返す。

At this time, if the order m is increased, the target signal of adjacent frequency components or higher will be approximated, so it is necessary to set it to a low order (for example, about 1 to 3) so as not to suppress the expected target signal. By subtracting the approximate expression calculated here from the original signal, low frequency components are suppressed (34a). Repeat this for every sweep.

This signal is a real signal, and a complex signal is required to perform phase monopulse processing (see Non-Patent Document 2). For this purpose, fast-time axis FFT (complex number) is performed (35a). In phase monopulse processing, the antenna aperture is divided (left and right, top and bottom, etc.) and the sum signal Σ and difference signal (left and right or top and bottom) Δ of the divided signals are required. For simplicity, only the Σ system is shown. If there is a Δ signal, the reception system (low noise amplifier 17 to frequency processing unit 38) is increased by the number of Δ signals and is input to the distance measurement/velocity measurement/angle measurement processing 37.

The signal obtained by fast-time axis FFT of real numbers has positive and negative components, as shown in Figure 11(b), so in order to convert it into a complex signal, first, as shown in Figure 11(c), , the negative (positive) signal components are set to 0 (38). To obtain a complex signal on the fast-time axis from this signal, an inverse FFT is performed on the fast-time axis as shown in Figure 11(d), but in the system shown in Figure 10, the frequency on the fast-time axis remains unchanged. In order to perform CFAR processing, inverse FFT processing is not included. The fast-time axis cells detected through detection processing by the CFAR 36a are subjected to FMCW ranging/velocity measurement processing and angle measurement processing, and are output as target information (37). The calculation formulas for distance and speed are the same as in the second embodiment, so their explanation will be omitted here. Regarding the angle measurement processing, assuming phase monopulse processing using the Σ beam and the Δ beam shown in FIG. 12(a), calculations are performed using the error voltage of the following equation.

このように、簡易な周波数変換器を用いても、予め、アンテナ１１のΣビームとΔビームの角度応答信号を測定して図１２（ｂ）の測角曲線を算出しておき、CFARにより検出したfast-time軸（fast-time軸FFT後の周波数軸）のセルについて、上記の誤差電圧εを観測すれば、測角値θを得ることができる。

In this way, even if a simple frequency converter is used, the angle response signals of the Σ beam and Δ beam of the antenna 11 are measured in advance to calculate the angle measurement curve shown in FIG. By observing the above error voltage ε for the fast-time axis (frequency axis after fast-time axis FFT) cell, the angle measurement value θ can be obtained.

As described above, the radar device according to this embodiment uses a low-order approximation curve of the real signal on the fast-time axis, so it suppresses clutter and proximity reflection signals while maintaining the low-speed target signal. Therefore, only low-speed targets can be detected.

(Fourth embodiment)
A radar device according to a fourth embodiment will be described with reference to FIGS. 13 to 16.
In the first embodiment, a method was described in which a low-speed target is detected by forming a null in the range-Doppler axis (FIG. 5(b)) for low frequency components such as clutter. If a null is formed on the range-Doppler axis and CA (Cell-Averaging)-CFAR (see Non-Patent Document 3) is performed on the Doppler axis for each range cell, false detection may occur due to the edge of the null. In this embodiment, countermeasures will be described.

13 to 16 show the configuration and processing example of a radar device according to the fourth embodiment, FIG. 13 is a block diagram showing the configuration of a transmitting system and a receiving system, and FIG. 14 shows a configuration centered on 0 Doppler. Range-Doppler diagram showing the range of GO (Greatest Of)-CFAR and the range of CA-CFAR, Figure 15 is a block diagram showing the CA-CFAR method and GO-CFAR method, and Figure 16 is the case of CA-CFAR. FIG. 4 is a waveform chart showing a comparison of processing near the null edge in the case of GO-CFAR and GO-CFAR.

The configurations of the transmission system and reception system shown in FIG. 13 are the same as those in the first embodiment except for the processing for CFAR detection. In FIG. 13, the same parts as in FIG. 1 are given the same reference numerals, and their explanations will be omitted. The difference is that the output of the slow-time FFT processing unit 25 is input to the CFAR type switching processing unit 28, and either GO-CFAR or CA-CFAR is selected according to predetermined conditions, and the CFAR of the selected type is The reason is that the processing is executed by the CFAR processing section 26a.

The conditions for the above CFAR types will be explained. First, a predetermined width is set around 0 Doppler as the low frequency component of Doppler. Since the Doppler resolution is determined by the reciprocal of the CPI time, the predetermined width is set to ±M times the reciprocal of the CPI time (for example, M=10, etc.). As shown in FIG. 14, GO-CFAR is selected within a predetermined width centered on 0 Doppler, and CA-CFAR is selected elsewhere. CA-CFAR is a method of dividing a test cell by the average amplitude of reference cells on both sides of the test cell, as shown in FIG. 15(a). On the other hand, GO-CFAR is a method of dividing the test cell by the maximum value of the reference cells on both sides of the test cell, as shown in FIG. 15(b). FIG. 16 shows the operation when there is a clutter suppression null. In the case of CA-CFAR shown in FIG. 16(a), the threshold is calculated while sequentially sliding the test cell and the reference cell on the fast-time axis. In this case, if there is a null, the average value of the reference cells on both sides will decrease, the threshold will decrease, and false detection may occur near the edge of the null. On the other hand, in the case of GO-CFAR shown in FIG. 16(b), since the value is the maximum value of the reference cells on both sides, amplitude reduction due to nulls is less likely to occur. Therefore, the threshold remains high even near the null edge, making it possible to suppress false detections.

However, although GO-CFAR is effective for suppressing false detection near nulls, the threshold tends to rise, so it is more likely to cause signal loss than CA-CFAR. Therefore, it is recommended to use GO-CFAR near the null and CA-CFAR outside that range.

As described above, in the radar device according to the present embodiment, even if a null is formed on the Doppler frequency axis due to suppression of clutter or proximity reflections and false detection occurs due to the influence of the null, GO-CFAR can be used to prevent false detection. Detection can be suppressed to detect only low-speed targets.

(Fifth embodiment)
A radar device according to a fourth embodiment will be described with reference to FIGS. 17 and 18.
In the fourth embodiment, a method has been described in which the CFAR of one axis of the Doppler frequency axis is switched in order to suppress false detection due to clutter null. In this embodiment, another method will be described.

17 and 16 show the configuration and processing example of a radar device according to the fifth embodiment, FIG. 17 is a block diagram showing the configuration of the transmitting system and the receiving system, and FIG. 18 is a two-dimensional range-Doppler axis It is a range-Doppler diagram showing the state of processing when CFAR is applied.

The configurations of the transmission system and reception system shown in FIG. 17 are the same as those in the first embodiment and the fourth embodiment except for the processing for CFAR detection. In FIG. 13, the same parts as in FIGS. 1 and 13 are designated by the same reference numerals, and the explanation thereof will be omitted. The difference is that a range-Doppler axis two-dimensional CFAR processing unit 26b is used to execute processing corresponding to the type of CFAR. As shown in Figure 18, two-dimensional CFAR is a method of setting a two-dimensional reference cell around a test cell and calculating CFAR using the average value (CA-CFAR) or maximum value (GO-CFAR) of the reference cell. can be applied (see Non-Patent Document 4). The CFAR switching method is the same as in the fourth embodiment. Compared to one-dimensional CFAR, it has a larger number of reference cells and is less susceptible to the effects of clutter suppression nulls, so only CA-CFAR may be selected for the entire range-Doppler range.

As described above, in the radar device according to the present embodiment, even if a null is formed on the Doppler frequency axis due to the suppression of clutter and proximity reflections and false detection occurs due to the influence of the null, by using two-dimensional CFAR, It is possible to suppress false detections and detect only low-speed targets.

According to the radar device according to the above embodiment, the N (N≧1) order approximate curve is calculated from the complex signal on the fast-time axis, and the low-frequency signal component ( Clutter, proximity reflections, etc.) are suppressed and signal processing (pulse compression, CFAR, etc.) is performed, so even if the target is moving at low speed, its position can be detected with higher accuracy.

It should be noted that the present invention is not limited to the above-described embodiments as they are, but can be embodied by modifying the constituent elements within the scope of the invention at the implementation stage. Moreover, various inventions can be formed by appropriately combining the plurality of components disclosed in the above embodiments. For example, some components may be deleted from all the components shown in the embodiments. Furthermore, components from different embodiments may be combined as appropriate.

11, 11a... Transmission signal generator, 12... DA converter, 13... Frequency converter, 14... High output amplifier, 15... Circulator, 16... Antenna, 17... Low noise amplifier, 18, 18a, 18b... Frequency converter , 19, 19a...AD converter,
21... CPI signal input section, 22... slow-time signal extraction section, 23... approximate curve calculation section, 24... approximate curve subtraction section, 25... slow-time FFT processing section, 26, 26a, 26b... CFAR processing section, 27 ... Distance measurement/angle measurement processing section, 28... CFAR type switching processing section,
31... CPI signal input section, 32... fast-time signal extraction section, 33... approximate curve calculation section, 34... approximate curve subtraction section, 35... fast-time FFT processing section, 36, 36a... CFAR processing section, 37... measurement Distance/speed measurement/angle measurement processing section, 38...frequency processing section.

Claims (6)

The reception system receives the reflected signals of the transmission pulses that are transmitted in one scanning period in the range direction from the transmission system and has N (N≧1) hits. a CPI signal extraction unit that extracts a CPI (Coherent Pulse Interval) signal corresponding to the reception interval ;
a slow-time signal extraction unit that extracts a slow-time axis complex signal for each range cell from the CPI signal;
an approximate curve calculation unit that calculates an m (m≧1) order approximate curve of the complex signal on the slow-time axis;
an approximate curve subtraction unit that suppresses low frequency components by subtracting the complex signal of the approximate curve from the original slow-time axis complex signal;
The slow-time axis complex signal in which the low frequency components have been suppressed is converted into a frequency domain signal, and the converted slow-time axis complex signal is centered at 0 Doppler on the Doppler frequency axis for each range cell. Then, within a predetermined frequency cell width, select GO (Greatest Of)-CFAR (Constant False Alarm Rate), which divides the test cell by the maximum amplitude value of the reference cells on both sides of the test cell. Otherwise, select CA (Cell-Averaging)-CFAR that divides the test cell by the amplitude average of the reference cells on both sides of the test cell, and detect the range-Doppler cell where the target exists by executing each CFAR process. and a target detection unit that subjects the detected range-Doppler cell to distance measurement and angle measurement processing and outputs it as target information . The reception system receives the reflected signals of the transmission pulses that are transmitted in one scanning period in the range direction from the transmission system and has N (N≧1) hits. a CPI signal extraction unit that extracts a CPI (Coherent Pulse Interval) signal corresponding to the reception interval;
a slow-time signal extraction unit that extracts a slow-time axis complex signal for each range cell from the CPI signal;
an approximate curve calculation unit that calculates an m (m≧1) order approximate curve of the complex signal on the slow-time axis;
an approximate curve subtraction unit that suppresses low frequency components by subtracting the complex signal of the approximate curve from the original slow-time axis complex signal;
The slow-time axis complex signal in which the low frequency components have been suppressed is converted into a frequency domain signal, and the converted slow-time axis complex signal is centered at 0 Doppler on the Doppler frequency axis for each range cell. CFAR (Constant False Alarm Rate) is a two-dimensional CFAR (Constant False Alarm Rate : constant false alarm rate) processing to detect the range-Doppler cell where the target is present, and process the detected range-Doppler cell for distance measurement and angle measurement and output it as target information.
A radar device equipped with . The reflected signal of the transmitted signal, which is transmitted from the transmitting system during one scanning period in the range direction and whose frequency modulation is a continuous N (N≧1) sweep , is received by the receiving system and is combined with the local frequency signal that matches the frequency modulation at the time of transmission. a CPI signal extracting unit that extracts a CPI (Coherent Pulse Interval) signal corresponding to each reception period of the real N sweep transmission signal from the mixed beat frequency reception signal;
a fast-time signal extraction unit that extracts a fast-time axis real number signal for each sweep number on the slow-time axis from the CPI signal;
an approximate curve calculation unit that calculates an m-th (m≧1) order approximate curve of the real signal on the fast-time axis;
an approximate curve subtraction unit that suppresses low frequency components by subtracting the real signal of the approximate curve from the original fast-time axis real signal;
The real signal on the fast-time axis in which the low frequency components have been suppressed is converted to a signal in the complex frequency domain, and the positive or negative frequency components of the complex signal on the fast-time axis converted to the frequency domain are set to 0. Convert it to a complex signal, perform CFAR (Constant False Alarm Rate) processing to detect the fast-time axis cell where the target exists, and measure the detected fast-time axis cell. / A radar device comprising a target detection unit that performs speed measurement processing and angle measurement processing and outputs the resultant target information . The reception system receives the reflected signals of the transmission pulses that are transmitted in one scanning period in the range direction from the transmission system and has N (N≧1) hits. Extract the CPI (Coherent Pulse Interval) signal corresponding to the reception interval ,
Extract the slow-time axis complex signal for each range cell from the CPI signal,
Calculate the m (m≧1) order approximate curve of the complex signal on the slow-time axis,
subtracting the complex signal of the approximate curve from the original slow-time axis complex signal to suppress low frequency components;
The slow-time axis complex signal in which the low frequency components have been suppressed is converted into a frequency domain signal, and the converted slow-time axis complex signal is centered at 0 Doppler on the Doppler frequency axis for each range cell. Then, within a predetermined frequency cell width, select GO (Greatest Of)-CFAR (Constant False Alarm Rate), which divides the test cell by the maximum amplitude value of the reference cells on both sides of the test cell. Otherwise, select CA (Cell-Averaging)-CFAR that divides the test cell by the amplitude average of the reference cells on both sides of the test cell, and detect the range-Doppler cell where the target exists by executing each CFAR process. Then, the detected range-Doppler cell is subjected to ranging and angle measurement processing and output as target information.
Radar signal processing method for radar equipment. The reception system receives the reflected signals of the transmission pulses that are transmitted in one scanning period in the range direction from the transmission system and has N (N≧1) hits. Extract the CPI (Coherent Pulse Interval) signal corresponding to the reception interval,
Extract the slow-time axis complex signal for each range cell from the CPI signal,
Calculate the m (m≧1) order approximate curve of the complex signal on the slow-time axis,
subtracting the complex signal of the approximate curve from the original slow-time axis complex signal to suppress low frequency components;
The slow-time axis complex signal in which the low frequency components have been suppressed is converted into a frequency domain signal, and the converted slow-time axis complex signal is centered at 0 Doppler on the Doppler frequency axis for each range cell. CFAR (Constant False Alarm Rate) is a two-dimensional CFAR (Constant False Alarm Rate (constant false alarm rate) processing to detect the range-Doppler cell where the target exists, process the detected range-Doppler cell for distance measurement and angle measurement, and output it as target information . Radar signal of the radar device Processing method. The reflected signal of the transmitted signal, which is transmitted from the transmitting system during one scanning period in the range direction and whose frequency modulation is a continuous N (N≧1) sweep , is received by the receiving system and is combined with the local frequency signal that matches the frequency modulation at the time of transmission. Extracting a CPI (Coherent Pulse Interval) signal corresponding to each reception period of the real N sweep transmission signal from the beat frequency reception signal by mixing ,
Extract the fast-time axis real number signal for each sweep number on the slow-time axis from the CPI signal,
Calculate the m (m ≧ 1) order approximate curve of the real signal on the fast-time axis,
subtracting the real number signal of the approximate curve from the original fast-time axis real number signal to suppress low frequency components;
The real signal on the fast-time axis in which the low frequency components have been suppressed is converted to a signal in the complex frequency domain, and the positive or negative frequency components of the complex signal on the fast-time axis converted to the frequency domain are set to 0. Convert it to a complex signal, perform CFAR (Constant False Alarm Rate) processing to detect the fast-time axis cell where the target exists, and measure the detected fast-time axis cell. / Perform speed measurement processing and angle measurement processing and output as target information
Radar signal processing method for radar equipment.

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