Radar system and radar signal processing method

Abstract

To reduce loss by performing integration with low processing scale and high efficiency even in a long-time integration.SOLUTION: According to an embodiment, in a radar system in which a reflection wave of a single pulse or a modulated N (N≥2) pulse transmitted from a transmission system is received by a reception system and subjected to coherent integration processing on a slow-time axis, the reception system divides the CPI of the received signal into M (M≥2), generates range-Doppler data in M division units to tentatively detect a cell of a reflection point, performs correlation processing between the divided CPI for each of Q (Q≥1) tentatively detected cells for each divided CPI, changes the phase from 0 to 360 degrees as P (P≥1), adds the phase, performs vector synthesis using a phase term for which the addition result is maximized by the phase search processing, and detects a target using the vector synthesis result.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present embodiment relates to a radar system and a radar signal processing method for detecting small targets at long distances. [Background technology]

[0002] In conventional radar systems, when the number of integration hits is large or when long-term integration is performed with a long PRI (Pulse Repetition Interval) and a long CPI (Coherent Pulse Interval), integration loss occurs due to range walk and Doppler walk.

[0003] Countermeasures for this problem include the integral sequence maximization method disclosed in Patent Document 1 and the integral sequence maximization (velocity / acceleration correction) disclosed in Patent Document 2. The method in Patent Document 1 utilizes the entire chirp band, performs zero-padding on the range frequency axis to pseudo-enhance resolution, and then maximizes the integral sequence on the slow-time axis using a search method. However, with this method, if the range walk is large, the range of the search method increases, resulting in an increase in processing scale. Meanwhile, the method in Patent Document 2 maximizes the integral sequence using a velocity and acceleration search method. However, even with this method, if the range walk is large, the range of the search method increases, resulting in an increase in processing scale. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 4881239 [Patent Document 2] Patent No. 5025403 [Patent Document 3] Patent No. 5072694 [Non-patent literature]

[0005] [Non-Patent Document 1] SAR method (pulse compression) Ouchi, 'Fundamentals of Synthetic Aperture Radar for Remote Sensing', Tokyo Denki University Press, pp.131-149 (2003) [Non-patent document 2] CFAR (Constant False Alarm Rate), Yoshida, 'Revised Radar Technology', Institute of Electronics, Information and Communication Engineers, pp.87-89 (1996) [Non-patent document 3] DBSCAN (Density-based Spatial Clustering of Applications with Noise), Sebastian Raschka, 'Python Machine Learning Programming', Impress, pp.319-323 (2016) [Non-patent document 4] Correlation Tracking, Yoshida, 'Revised Radar Technology', Institute of Electronics, Information and Communication Engineers, pp.254-259 (1996) [Non-Patent Document 5] Nearest Neighbor (NN) correlation processing, Samuel S. Blackman, 'Design and Analysis of Modern Tracking Systems', Artech House, pp.8-11 (1999) Summary of the Invention [Problem to be solved by the invention]

[0006] As mentioned above, conventional radar systems have a problem in that integration loss occurs due to range walk and Doppler walk when performing long-term integration.When the range walk is large, which is a method for maximizing the integral sequence, the range of the search method increases, which increases the processing scale.

[0007] An object of this embodiment is to provide a radar system and a radar signal processing method that can perform integration with high efficiency and a small processing scale even during long-term integration, thereby reducing loss. [Means for solving the problem]

[0008] In order to solve the above problem, this embodiment is a radar system in which a single pulse or a reflected wave of modulated N (N≧2) pulses transmitted from a transmission system is received by a reception system and subjected to coherent integration processing on a slow-time axis, and the reception system divides the CPI (Coherent Pulse Interval) of the received signal into M (M≧2) divisions, generates range-Doppler (RD) data for each of the M division units, tentatively detects cells of reflection points, and performs correlation processing between the divided CPIs for each of Q (Q≧1) tentatively detected cells for each divided CPI, Split CPI The phase is changed from 0 degrees to 360 degrees in P (P≧1) ways. , split CPI between The phase term that maximizes the sum is used to perform vector synthesis, and the target is detected using the result of this vector synthesis. In other words, by dividing a long-term CPI and integrating for each division, the influence of range walk is reduced, and then by performing phase search and integration between the divided CPIs, integration over all CPIs is performed efficiently.

[0009] In the receiving system, RD data is generated in the M division units and the reflection point cells are provisionally detected, and then cluster analysis is performed in each division unit to extract Q (Q≧1) clusters. After correlation processing between the division CPIs for each cluster, Split CPI The phase is changed from 0 degrees to 360 degrees in P (P≧1) ways. , split CPI between The phase term that maximizes the sum is used to perform vector synthesis, and the result of this vector synthesis is used to detect targets. In other words, by dividing a long-term CPI and integrating for each division, the effect of range walk is reduced, and after further reducing false detections through cluster analysis, phase search and integration between the divided CPIs is performed, thereby efficiently performing integration for all CPIs.

[0010] The phase search method involves selecting two CPIs, m and m+1 (m=1 to M-1), from the M division units in order, Split CPI The phase is changed from 0 degrees to 360 degrees in P (P≧1) ways. , split CPI betweenThe phase terms are added, vectors are synthesized using the phase term that maximizes the result of the addition, and the target is detected using the result of the vector synthesis.In other words, by performing a phase search for every two adjacent divided CPIs in the phase search when integrating between divided CPIs, integration can be performed efficiently even when the amount of movement of the range-Doppler cells between divided CPIs is large, such as in the case of a high-speed target, and the phase search table can be made smaller, reducing the processing scale.

[0011] The phase search method uses M division units, Split CPI The phase is changed from 0 degrees to 360 degrees in P (P≧1) ways. , add up between split CPI , P (M-1) Vectors are synthesized using the phase term that maximizes the sum of the three additions, and the target is detected using the result of the vector synthesis. In other words, by having a table of search phases for all divided CPIs in the phase search during integration between divided CPIs, it is possible to perform an optimal phase search between all CPIs and improve integration efficiency.

[0012] Furthermore, the phase search method involves performing coherent integration on the slow-time axis in each CPI division unit by performing FFT processing on the fast-time axis and converting it to the range frequency axis, then dividing the range frequency into Q (Q≧1) regions, and performing inverse FFT (narrowband pulse compression) on the signal in each band with all samples except for the band being zero-filled. The Q results of the FFT processing on the slow-time axis are then amplitude integrated for provisional detection, and phase search integration is performed using the RD data for each CPI division unit that has been range-walk corrected using a search method based on the provisional detection results. That is, by narrowing the band, the range resolution is reduced and the influence of range walk is reduced, and reflection points are provisionally detected using CFAR. The wideband high-resolution range data is used to limit the search range for provisional detection and reduce the processing scale, and then range walk correction is performed and FFT processing is performed on the slow-time axis. This allows efficient integration even within the divided CPI, and by combining it with subsequent phase search integration between division units, it becomes possible to maximize the integration efficiency for all CPIs. [Brief explanation of the drawings]

[0013] [Figure 1] FIG. 1 is a block diagram showing the configurations of a transmission system and a reception system of a radar system according to a first embodiment. [Figure 2] FIG. 2 is a flowchart showing a processing procedure of the reception system of the radar system according to the first embodiment. [Figure 3] FIG. 3 is a conceptual diagram showing the processing operation of the reception system in the first embodiment. [Figure 4] FIG. 4 is a diagram showing the tracking process by the NN correlation process applied to the first embodiment. [Figure 5] FIG. 5 is a block diagram showing the configurations of the transmission system and the reception system of the radar system according to the second embodiment. [Figure 6] FIG. 6 is a flowchart showing a processing procedure of the reception system of the radar system according to the second embodiment. [Figure 7] FIG. 7 is a conceptual diagram showing the processing operation of the reception system in the second embodiment. [Figure 8] FIG. 8 is a diagram illustrating a cluster analysis method using DBSCAN applied to the second embodiment. [Figure 9] FIG. 9 is a flowchart showing the process flow of the phase search method applied to the reception system of the radar system according to the third embodiment. [Figure 10] FIG. 10 is a flowchart showing the process flow of the phase search method applied to the reception system of the radar system according to the fourth embodiment. [Figure 11] FIG. 11 is a block diagram showing the configurations of the transmission system and the reception system of the radar system according to the fifth embodiment. [Figure 12] FIG. 12 is a flowchart showing a processing procedure of the reception system of the radar system according to the fifth embodiment. [Figure 13] FIG. 13 is a flowchart showing the processing procedure of range walk correction applied to the reception system of the fifth embodiment. [Figure 14]FIG. 14 is a diagram showing a processing example in which normal pulse compression processing is used in the reception system of the fifth embodiment. [Figure 15] FIG. 15 is a diagram illustrating an example of range walk correction processing applied to the reception system of the fifth embodiment. [Figure 16A] FIG. 16A is a diagram illustrating a processing example of the range walk correction shown in FIG. [Figure 16B] FIG. 16B is a diagram illustrating a processing example of the range walk correction shown in FIG. DETAILED DESCRIPTION OF THE INVENTION

[0014] Hereinafter, embodiments will be described with reference to the drawings.

[0015] (First embodiment) The first embodiment will be described with reference to FIGS.

[0016] FIG. 1 is a block diagram showing the configuration of a radar system according to the first embodiment, where (a) is a block diagram showing the configuration of a transmission system, and (b) is a block diagram showing the configuration of a reception system.

[0017] In the transmission system shown in Figure 1(a), a signal generator 11 generates a transmission seed signal, a modulator 12 modulates and multiplexes transmission information onto the transmission seed signal, a frequency converter 13 converts the modulated signal into a high-frequency signal, a pulse modulator 14 pulse-modulates the high-frequency signal to generate a transmission pulse train, and N (N≧2) hit pulses are transmitted from a transmission antenna 15 at PRI (Pulse Repetition Interval) intervals.

[0018] 1(b), a reflected wave of a pulse signal transmitted from a transmitting antenna 15 is received by a receiving antenna 21, the received signal is frequency-converted to baseband by a frequency converter 22, and converted to a digital signal by an AD converter 23 to obtain CPI (Coherent Pulse Interval) signals (fast-time and slow-time signals). Subsequently, the CPI signal output from the AD converter 23 is divided into M (M≧1) ways by a CPI divider 24, pulse compression is performed for each CPI division unit by a pulse compressor 25 (see Non-Patent Document 1), and an FFT process on the slow-time axis is performed by a slow-time axis FFT processor 26 to obtain M ways of range-Doppler (RD) data. Next, temporary detector 27 performs temporary detection processing using CFAR (see Non-Patent Document 2) or the like to temporarily detect cells having reflection point observation values, and phase search integrator 28 performs correlation processing based on the similarity between the temporarily detected cells to obtain correlation results between the divided CPIs for the number Q (Q≧1) of temporary detections and performs phase search integration. After the results of this phase search integration are replaced with the original RD data, detector 29 detects targets using CFAR or the like and outputs target information such as the position and speed of the detected targets.

[0019] The transmission system and the reception system may be integrated or may be installed at separate locations.

[0020] The processing operation of the radar system configured as above will be described with reference to Figures 2 to 4. Figure 2 is a flowchart showing the processing procedure of the reception system of the radar system according to this embodiment, Figure 3 is a conceptual diagram showing the processing operation of the reception system of this embodiment, and Figure 4 is a diagram showing the tracking process by NN correlation processing applied to this embodiment.

[0021] When N (N≧2) hit pulse signals are transmitted at PRI intervals from transmitting antenna 15 in the transmitting system, reflected waves of the transmitted pulse signals are received by receiving antenna 21 in the receiving system, and the received signals are frequency-converted to baseband by frequency converter 22 and converted to digital signals by AD converter 23 to obtain CPI signals, followed by the signal processing shown in Fig. 2. In this signal processing, the CPI signal output from AD converter 23 is divided into M (M≧1) ways by CPI divider 24 (step S11), pulse compressor 25 compresses the pulses for each division unit (step S12), slow-time axis FFT processor 26 performs FFT processing on the slow-time axis to obtain M sets of RD data (step S13), and temporary detector 27 provisionally detects cells having reflection point observation values ​​for each RD data using CFAR or the like (step S14).

[0022] The processing of steps S12 to S14 is executed sequentially in CPI division units (steps S15 and S16), and when processing for all division units is completed, phase search integrator 28 performs correlation processing on the input RD data based on the similarity between provisionally detected cells (step S17), obtains correlation results between the provisionally detected number Q (Q≧1) of divided CPIs, and performs phase search integration (steps S18 to S20), and replaces the results of this phase search integration between the divided CPIs with the original RD data (RD data synthesis within CPI) (step S21). The RD data synthesis output obtained in this way is input to detector 29, which detects targets using CFAR or the like, and outputs target information such as the position and speed of the detected target (step S22), thereby completing the series of processes.

[0023] Here, we will explain the long-term integration method used in the above signal processing. If data is acquired in range cell units within the PRI for each pulse transmitted at PRI intervals, target range walk will occur if the CPI is long. In this case, loss will occur even if FFT processing is performed directly on the slow-time axis, so a countermeasure is required.

[0024] Therefore, in this embodiment, as shown in FIG. 3(a), the CPI is divided into M (M≧1) ways, and as shown in FIG. 3(b), pulse compression and slow-time axis FFT processing are performed for each CPI division unit to obtain M types of RD data. For each RD data, search integration is performed for each CPI division unit as shown in FIG. 3(c), and reflection point observation values ​​are provisionally detected using CFAR or the like as shown in FIG. 3(d). In this case, because the SN (signal-to-noise ratio) of the RD data is low for each CPI division unit, the detection rate is improved by setting a lower than normal amplitude threshold to allow for false detections. Thus, when provisional detection is performed for each divided CPI, the provisional detection results for each divided CPI are different. Therefore, correlation processing is performed between provisionally detected cells in the RD data based on the similarity, and correlation results are obtained for the provisional detection number Q (Q≧1) of divided CPIs. For example, assuming that Q pieces of RD data for each divided CPI are an M sequence, correlation tracking processing (see Non-Patent Document 4) can be used to obtain Q correlation results for each provisional detection.

[0025] Specifically, a common NN (Nearest Neighbor) correlation tracking process (Non-Patent Document 5) shown in FIG. 4 can be used. This NN correlation tracking process calculates a predicted value for the next cycle based on an assumed motion model using the smoothed value for each cycle, sets a correlation gate around the predicted value, and extracts the observed value closest to the predicted value as an NN value from among the observed values ​​within the correlation gate. Next, a smoothed value is calculated based on the predicted value and the NN value, and the process of calculating the predicted value for the next cycle is repeated. If there are multiple tracks (smoothed values), the above process is repeated for each track. In this embodiment, each cycle corresponds to the order of each unit obtained by dividing the slow-time axis, and each division unit is associated with each provisional detection. This has the advantage that correlation tracking can accurately process correlation even when the divided CPI time is long due to long-term integration and the provisional detection cell moves between each divided CPI.

[0026] The phases between the Q divided CPIs for each provisional detection are different. Therefore, to obtain the vector synthesis result, a phase search integration is performed. Specific techniques for this phase search integration will be described in the third and fourth embodiments. After the result of this phase search integration is replaced with the original RD data, targets are detected using CFAR or the like.

[0027] As mentioned above, when pulse compression and slow-time axis FFT processing are performed for each CPI division unit, the SN is low for each CPI division unit, resulting in false detections due to clutter and other factors in addition to targets. In response to this, searching for phase terms and combining vectors can improve the SN, making target detection easier. While each target is depicted as a single point in Figure 3 for clarity, in reality, multiple cells are contained around a single target. By replacing this integration result with RD data, targets can be detected with a high SN using CFAR, multiple maximum value detection, etc.

[0028] As described above, in the radar system according to this embodiment, the receiving system receives the reflected waves of a single pulse or modulated N (N≧2) pulses transmitted from the transmitting system and performs coherent integration processing on the slow-time axis. In the receiving system, the CPI of the received signal is divided into M (M≧2) parts, RD data is generated for each of the M division units to tentatively detect reflection point cells, and for each of the Q (Q≧1) tentatively detected cells for each divided CPI, correlation processing is performed between the divided CPIs, and the phase is changed P (P≧1) times from 0 degrees to 360 degrees and added, and vector synthesis is performed using the phase term that maximizes the summation result. Targets are detected using the vector synthesis result. In this way, by dividing the long-term CPI and integrating for each division unit, the influence of range walk is reduced, and further, by performing phase search and integration between the divided CPIs, integration over all CPIs can be efficiently performed.

[0029] (Second embodiment) The second embodiment will be described with reference to FIGS.

[0030] FIG. 5 is a block diagram showing the configuration of a transmission system and a reception system of a radar system according to a second embodiment, where (a) is a block diagram showing the configuration of the transmission system and (b) is a block diagram showing the configuration of the reception system. FIG. 6 is a flowchart showing the processing procedure of the reception system of the radar system according to the second embodiment. In FIGS. 5 and 6, the same parts as those in FIGS. 1 and 2 are designated by the same reference numerals, and redundant explanations will be omitted here. FIG. 7 is a conceptual diagram showing the processing operation of the reception system in the second embodiment, and FIG. 8 is a diagram showing a cluster analysis method using DBSCAN applied to the second embodiment.

[0031] This embodiment differs from the first embodiment in that a cluster analyzer 30 is disposed between the slow-time axis FFT processor 26 and the temporary detector 27 in the receiving system shown in FIG. 5(b). As shown in FIG. 6, after slow-time axis FFT processing (step S13), cluster analysis is performed using a predetermined cluster analysis method (step S23), and the analysis results are input to the temporary detector 27. In the first embodiment, only pulse compression and slow-time axis FFT processing are performed on the signal before phase search integration. In this case, the range-Doppler cells used in phase search integration include not only target candidates but also false detections, which increases the processing scale of the subsequent correlation processing between temporary detections and phase search integration processing. In the second embodiment, as a method for suppressing this increase in processing scale, cluster analysis is performed on the RD data that has been pulse compressed and processed by the slow-time axis FFT for each divided CPI.

[0032] Specifically, as shown in Figure 7(a), the CPI is divided into M (M≧2) ways, and as shown in Figure 7(b), pulse compression and slow-time axis FFT processing are performed for each CPI division unit to obtain M ways of RD data. After performing cluster analysis on each RD data as shown in Figure 7(c), search integration is performed as shown in Figure 7(d), and then reflection point observation values ​​are provisionally detected using CFAR or the like as shown in Figure 7(e).

[0033] One example of a method using the cluster analysis is DBSCAN (Non-Patent Document 3) shown in Figure 8. This method forms clusters so that border points of MinPts points exist within a radius ε of a core point. Setting two parameters, the radius ε and the number of MinPts points, can suppress false positives. Figure 7(c) shows this process. It can be seen that clusters are extracted by taking advantage of the fact that there are multiple reflection points around a single target, but false positives are low. Using these clusters, correlation processing is performed between divided CPIs to associate each target, and then phase search integration is used, just as in the first embodiment. In the case of clusters, since there are multiple reflection points for each target, the correlation processing can be simplified by performing center of gravity calculations among the multiple reflection points to combine them into a single point. This allows targets in the RD data for each divided CPI to be efficiently integrated and detected using CFAR, multiple maximum value detection, etc.

[0034] As described above, in this embodiment, the receiving system generates RD data for M division units to provisionally detect reflection point cells, then performs cluster analysis for each division unit to extract Q (Q≧1) clusters, and for each cluster, performs correlation processing between the divided CPIs, then changes the phase from 0 degrees to 360 degrees in P (P≧1) ways and adds them, performs vector synthesis using the phase term that maximizes the addition result, and detects the target using the vector synthesis result. In this way, by dividing a long-term CPI and integrating for each division unit, the influence of range walk is reduced, and further, erroneous detection is reduced by cluster analysis, and then phase search and integration between the divided CPIs is performed, making it possible to efficiently perform integration over all CPIs.

[0035] (Third embodiment) In the third embodiment, a specific example of the above-mentioned phase search method will be described with reference to Fig. 9. Fig. 9 is a flowchart showing the processing flow of the phase search method applied to the reception system of the radar system according to the third embodiment. In Fig. 9, the same parts as in Fig. 6 are denoted by the same reference numerals, and only different parts will be described here.

[0036] The phase search method of this embodiment corresponds to steps S24 to S29 in Fig. 9. That is, after performing correlation between tentative detections (step S17), a phase search is performed using phase-corrected integration (step S24), and the phase is sequentially changed from 0 degrees to 360 degrees to select the phase with the maximum value (steps S25 to S27). The processes of steps S24 to S27 are executed while sequentially changing the CPI division unit (steps S28 and S29), and then the process proceeds to step S19.

[0037] Here, the phase search method in step S24 is generally a process in which RD data for each CPI division unit is generated, and then correlation processing is performed for each provisionally detected point using the provisional detection results. However, in this embodiment, a method is used in which the divided CPIs are sequentially phase-corrected and added. This is an advantageous method for combining RD data that are not separated in time when the target is moving quickly and correlation processing does not work well. In other words, for the addition results up to the mth divided CPI number, the phase of the next (m+1)th RD data is changed to search for the maximum phase. This process is expressed by the following equation.

[0038]

number

[0039] As described above, in the phase search method according to this embodiment, two CPIs, m and m+1 (m=1 to M-1), are selected from the M division units in order, the phase is changed from 0 degrees to 360 degrees in P (P≧1) ways, and added together, vectors are synthesized using the phase term that maximizes the result of the addition, and the target is detected using the result of the vector synthesis.

[0040] That is, in the phase search for integration between divided CPIs, by performing a phase search for every two adjacent divided CPIs, integration can be performed efficiently even when the amount of movement of the range-Doppler cells between divided CPIs is large, such as in the case of a high-speed target, and the phase search table can be made smaller, thereby reducing the processing scale.

[0041] (Fourth embodiment) In the fourth embodiment, a specific example of the phase search method described above will be described with reference to Fig. 10. Fig. 10 is a flowchart showing the processing flow of the phase search method applied to the reception system of the radar system according to the third embodiment. In Fig. 10, the same parts as in Fig. 6 are denoted by the same reference numerals, and only the different parts will be described here.

[0042] In the third embodiment, a method of sequentially using divided CPIs during phase search and integration was described. On the other hand, when the target moving speed is slow, a method of correcting the phase and integrating over the entire divided CPI can also be considered. In the fourth embodiment, a phase search method for when the target moving speed is slow will be described.

[0043] The phase search method of this embodiment corresponds to steps S24, S25, S27, and S30 in Fig. 10. That is, after performing correlation between tentative detections (step S17), a phase search is performed using phase-corrected integration (step S24), the phase is changed in the range from 0 to 360 degrees over the entire divided CPI according to a preset phase table (step S30), and the phase with the maximum value is selected (step S27). After performing the processes of steps S24, S25, S27, and S30, the process proceeds to step S19.

[0044] That is, in this embodiment, for the addition results up to the mth divided CPI number, the phase of the next (m+1)th RD data shown in the phase table is changed to search for the phase that will be the maximum value.

[0045]

number

[0046] The search phase table is P (M-1) This results in a phase table of 1000 phases. Of these 1000 phases, the 1000 that maximizes RDsum(1000, q) is selected. In this case, the phases are corrected and integrated simultaneously across all M divided CPIs, allowing for the selection of the optimal integral. This maximum value allows for the synthesis of high SN RD data, making it possible to perform detection using CFAR or multiple maximum value detection.

[0047] As described above, the phase search method applied to this embodiment uses M division units, changes the phase from 0 degrees to 360 degrees in P (P≧1) ways, and finds P (M-1) Vectors are synthesized using the phase term that maximizes the sum of the three additions, and the target is detected using the result of the vector synthesis.By having a table of search phases for all divided CPIs, the optimal phase search can be performed between all CPIs during phase search during integration between divided CPIs, making it possible to improve integration efficiency.

[0048] (Fifth embodiment) In the first to fourth embodiments, RD data is obtained by pulse compression for each CPI and slow-time axis FFT processing. However, when the target is moving at an extremely high speed, range walk may occur even within the divided CPI. In the fifth embodiment, a countermeasure for this problem will be described with reference to FIGS. 11 to 16.

[0049] Fig. 11 is a block diagram showing the configuration of a transmission system and a reception system of a radar system according to a fifth embodiment, where (a) is a block diagram showing the configuration of the transmission system and (b) is a block diagram showing the configuration of the reception system. Fig. 12 is a flowchart showing the processing procedure of the reception system of the radar system according to the second embodiment. In Figs. 11 and 12, the same parts as in Figs. 5 and 6 are designated by the same reference numerals, and redundant explanations will be omitted here.

[0050] 13 is a flowchart showing the processing procedure of range walk correction applied to the receiving system of the fifth embodiment, FIG. 14 is a diagram showing an example of processing when normal pulse compression processing is used in the receiving system of the fifth embodiment, FIG. 15 is a diagram showing an example of processing of range walk correction applied to the receiving system of the fifth embodiment, and FIGS. 16A and 16B are diagrams showing an example of processing of range walk correction shown in FIG. 15.

[0051] This embodiment differs from the second embodiment in that, in the receiving system of FIG. 11(b), after processing by the CPI divider 24, narrowband range compression is performed by the narrowband range compressor 31, slow-time axis FFT processing is performed by the slow-time axis FFT processor 32, integration processing is performed by the amplitude integrator 33, and then cells of the reflection point observation values ​​are provisionally detected by the temporary detector 34, while the wideband range compressor 35 range compresses the divided CPI output, and the range walk of the provisionally detected cells acquired by the temporary detector 34 is corrected by the range walk corrector 36 before being sent to the slow-time axis FFT processor 26. Also, in the flowchart shown in FIG. 12, after pulse compression processing (step S12), range walk correction is performed (step S28) and the system proceeds to slow-time axis FFT processing (step S13).

[0052] First, in the case of normal pulse compression (see Non-Patent Document 1), processing is performed as shown in FIG. 14. Pulse compression is a correlation process between an input signal and a range compression signal. To perform this in the frequency domain, the received pulse signal shown in FIG. 14(a1) and the reference signal shown in FIG. 14(a2) are each subjected to FFT processing on the fast-time axis to obtain the signals shown in FIG. 14(b1) and (b2). Next, as shown in FIG. 14(c), conjugate multiplication is performed, followed by fast-time axis inverse FFT processing to obtain the pulse-compressed waveform shown in FIG. 14(d). Here, if the pulse width after pulse compression is narrower than the target movement, limiting the bandwidth and lowering the range resolution can suppress the effects of range walk. For this reason, we consider pulse compression in a narrow, band-limited band, as shown in FIG. 15.

[0053] First, as shown in Figure 11, the process up to CPI division is the same as in the first and second embodiments. Next, the entire range frequency band is divided and pulse-compressed by narrowband pulse compressor 31. After FFT processing by slow-time axis FFT processor 32, each division unit is amplitude-integrated by amplitude integrator 33, and reflection point observation values ​​are provisionally detected by temporary detector 34. Meanwhile, pulse compression is performed using the entire band by wideband pulse compressor 35, and range walk correction (described later) is performed by range walk corrector 36 using the provisional detection results. Thereafter, as in the first and second embodiments, FFT processing of the slow-time axis is performed (26), and provisional detection is performed (27). Using this provisional detection result, phase-corrected integration between divided CPIs is performed (28), and detection by CFAR or the like is performed using high-SN RD data (29), thereby obtaining target information.

[0054] The range walk correction process in step S28 corresponding to the range hood temporary detector 34 and range walk corrector 36 is specifically performed as shown in FIG.

[0055] 13, first, a wideband signal is transmitted and received (step S41), divided into multiple narrowbands on the fast-time axis (step S42), narrowband compression is performed on the fast-time axis (step S43), and the narrowband compression process is repeated until it is completed for all narrowbands (steps S44 and S45). When compression processing for all narrowbands is completed, the amplitude of each compression process result is integrated (step S46), and tentative detection is performed using CFAR or the like (step S47), and wideband compression on the fast-time axis is performed before FFT processing on the slow-time axis (step S48).

[0056] Next, the maximum sequence of the slow-time axis compression result is extracted using the integral sequence search method (step S49), and range walk correction is performed to shift the integral sequence before slow-time axis FFT processing (step S50). The processes of steps S49 and S50 are repeated until the number of provisional detections obtained in step S49 is reached (steps S51 and S52). When the number of provisional detections has been reached, the signal is compressed to the fast-time axis wideband before slow-time axis FFT processing (step S53), and the process proceeds to step S13 and subsequent steps shown in FIG.

[0057] Next, a more specific processing will be described with reference to Fig. 15. First, band-limited narrowband pulse compression will be formulated. When the input signal and reference signal shown in Fig. 15(a1) and (a2) are subjected to FFT processing on the fast-time axis, the following equation is obtained, as shown in Fig. 15(b1) and (b2).

[0058]

number

[0059]

number

[0060]

number

[0061]

number

[0062] By using the above-described process using zero padding, the resolution of the range cells in narrowband range compression and wideband range compression can be made the same, and cells tentatively detected in narrowband range compression can be directly used in wideband range compression.

[0063] When frequency bands are divided, the SN ratio drops by the number of divisions compared to the entire frequency band. To prevent this drop in SN ratio, it is necessary to coherently combine the results of pulse compression for each divided frequency band, and the phase search method described in the first to fourth embodiments can be considered. However, since this increases the processing scale, amplitude integration is considered as a simpler method. This is a method in which the results for each frequency division unit are converted into amplitude and integrated (Fig. 15(f)). This result is used for provisional detection.

[0064] Next, wideband pulse compression is similar to the normal pulse compression shown in FIG. 14, and is as follows.

[0065]

number

[0066]

number

[0067] Next, range walk correction will be explained using Figures 16A and 16B. First, the narrowband range compression result is tentatively detected using CFAR or the like, and range cells are extracted for each tentative detection to obtain range cells Rm (m = 1 to Mt: Mt is the number of tentative detections) (Figure 16A(a)).

[0068] Next, wideband range compression is performed (Fig. 16B(d)). The slow-time axis uses the signal before FFT processing (RDwide). The Rp (p = 1 to P, P ≥ 1) cells are centered around the tentatively detected Rm cell. An integral series of N cells (Rm11 to RmPQ) with a gradient of Q (Q ≥ 1) passing through the selected range cell Rp is set (Fig. 16A(b)). Each integral series is range-walk corrected to become the Rm cell on the range axis, and then rearranged on the slow-time axis (Fig. 16A(c)). This series is then FFT-processed on the slow-time axis, and the integral series (before the slow-time axis FFT) with the largest maximum value among the P × Q results is selected (Fig. 16B(e)). Furthermore, after performing Doppler walk correction as necessary, the data of the range Rm × Doppler N cells in RDwide is replaced with the maximum integral sequence, and this process is repeated for Mt cells to obtain RDcal data (Fig. 16B(f)). Using this RDcal data, a slow-time axis FFT can be performed to obtain RD data with a high S / N ratio.

[0069] This RD data is used for tentative detection (27) (FIG. 16B(g)), and the phase search (28) described in the first to fourth embodiments is used to efficiently synthesize signals between divided CPIs. Detection processing (29) can be performed with high S / N ratio using CFAR or multiple maximum value detection, and target information can be obtained.

[0070] In the above example, only the range walk correction has been described, but a Doppler correction method for long-term integration (see Patent Document 3) may also be applied.

[0071] As described above, in this embodiment, when performing coherent integration on the slow-time axis for each CPI division unit in the phase search method, FFT processing is performed on the fast-time axis to convert it to the range frequency axis, and then the range frequency is divided into Q (Q≧1) regions. In each band, signals other than the band samples are zero-filled, and then an inverse FFT (narrowband pulse compression) is performed on the signal. The Q results of the FFT processing on the slow-time axis are amplitude integrated for provisional detection, and phase search integration is performed using the RD data for each CPI division unit that has been range-walk corrected using the search method based on the provisional detection results. Therefore, after narrowing the band to reduce the range resolution and the influence of range walk, reflection points are provisionally detected using CFAR. After limiting the search range for provisional detection using wideband high-resolution range data to reduce the processing scale, range walk correction is performed and FFT processing is performed on the slow-time axis. This allows efficient integration even within the divided CPI, and by combining it with subsequent phase search integration between division units, it is possible to maximize the integration efficiency for all CPIs.

[0072] The present invention is not limited to the above-described embodiments, and the components can be modified and embodied in practice without departing from the spirit of the invention. Furthermore, various inventions can be created by appropriately combining multiple components disclosed in the above-described embodiments. For example, some components may be omitted from all the components shown in the embodiments. Furthermore, components from different embodiments may be appropriately combined. [Explanation of symbols]

[0073] 11... signal generator, 12... modulator, 13... frequency converter, 14... pulse modulator, 15... transmitting antenna, 21...receiving antenna, 22...frequency converter, 23...AD converter, 24...CPI divider, 25...pulse compressor, 26...slow-time axis FFT processor, 27...temporary detector, 28...phase search integrator, 29...detector, 30...cluster analyzer, 31...narrowband range compressor, 32...slow-time axis FFT processor, 33...amplitude integrator, 34...temporary detector, 35...wideband range compressor, 36...range walk compensator.

Claims

1. A radar system in which a single pulse or a modulated N (N≧2) pulse reflected wave transmitted from a transmission system is received by a reception system and subjected to coherent integration processing on a slow-time axis, In the receiving system, the CPI (Coherent Pulse Interval) of the received signal is divided into M (M≧2) parts, range-Doppler data is generated in M ​​division units to tentatively detect reflection point cells, correlation processing is performed between the divided CPIs for each of Q (Q≧1) tentatively detected cells for each divided CPI, the phase of the divided CPI is changed in P (P≧1) ways from 0 degrees to 360 degrees, addition is performed between the divided CPIs, vectors are synthesized using the phase term that maximizes the addition result through phase search processing, and the target is detected using the vector synthesis result.

2. 2. The radar system according to claim 1, wherein the receiving system generates RD data for each of the M division units to tentatively detect reflection point cells, then performs cluster analysis for each division unit to extract Q (Q≧1) clusters, and for each cluster, performs correlation processing between the divided CPIs, then changes the phase of the divided CPI from 0 degrees to 360 degrees in P (P≧1) ways, adds the phases between the divided CPIs, and performs vector synthesis using the phase term that maximizes the result of the addition, and detects targets using the result of the vector synthesis.

3. 2. The radar system according to claim 1, wherein the phase search process is performed by selecting two CPIs, m and m+1 (m=1 to M-1), from the M division units, changing the phase of the divided CPIs in P (P≧1) ways from 0 degrees to 360 degrees, adding them between the divided CPIs, performing vector synthesis using the phase term that maximizes the result of the addition, and detecting targets using the result of the vector synthesis.

4. In the phase search process, the reception system uses M division units to change the phase of the divided CPI in P (P≧1) ways from 0 degrees to 360 degrees, and performs addition between the divided CPIs. （Ｍ－１） 2. The radar system according to claim 1, wherein vector synthesis is performed using a phase term that maximizes the sum of the three addition results, and the target is detected using the result of the vector synthesis.

5. 2. The radar system according to claim 1, wherein, as the phase search process, the receiving system performs coherent integration on the slow-time axis in each CPI division unit by performing FFT processing on the fast-time axis to convert to a range frequency axis, then divides the range frequency into Q (Q≧1), and in each band, performs inverse FFT on a signal in which samples other than those in the band are padded with zeros to perform narrowband pulse compression, and then amplitude integrates the Q results of the FFT processing on the slow-time axis to perform provisional detection, and performs phase search and integration using RD data for each CPI division unit that has been range walk corrected by phase search from the provisional detection results.

6. A radar signal processing method in which a single pulse or a reflected wave of modulated N (N≧2) pulses transmitted from a transmission system is received by a reception system and subjected to coherent integration processing on a slow-time axis, The radar signal processing method includes the steps of: in the receiving system, dividing the CPI (Coherent Pulse Interval) of the received signal into M (M≧2) parts; generating range-Doppler data in M ​​division units to tentatively detect cells of reflection points; performing correlation processing between the divided CPIs for each of Q (Q≧1) tentatively detected cells for each divided CPI; changing the phase of the divided CPI in P (P≧1) ways from 0 degrees to 360 degrees; adding the phases between the divided CPIs; performing vector synthesis using the phase term that maximizes the result of the addition through phase search processing; and detecting targets using the result of the vector synthesis.

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