Signal processor and pulse radar system

Abstract

To provide a signal processor that can detect targets in less time than before.SOLUTION: A signal processor 20 includes: a pre-measurement section 30 that calculates a plurality of pre-measurements that represents a distance between a pulse radar system 1 and one or more targets on the basis of a plurality of received signals; a distance candidate generation section 34 that generates a plurality of ambiguity values that represents candidates for the distance between the pulse radar system 1 and the one or more targets from the pre-measurements, using pulse repetition cycles corresponding to the pre-measurements; a target existence distribution generation section 35 that generates a target existence distribution with multiple localization distributions that indicate a probability that there will be one or more targets in each of a plurality of regions centered on the plurality of ambiguity values; an integration section 36 that calculates a cumulative distribution by integrating a plurality of target existence distributions; a target detection section 37 that estimates target information related to the one or more targets on the basis of one or more maximum peak values that appear in the cumulative distribution; and a transmission pulse selection section 38.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] This disclosure relates to a signal processor and pulse radar system for detecting targets using multiple types of pulse repetition intervals (PRI). [Background technology]

[0002] A pulse radar transmits a pulse train into space at a pulse repetition period corresponding to a predetermined pulse repetition frequency (PRF). It receives a reflected wave signal generated when the pulse train is reflected by a target within that space, and can measure the distance from the pulse radar to the target based on the delay time of the reflected wave signal. If the pulse radar has a function to detect the target's Doppler frequency, it can also measure the relative velocity of the target.

[0003] In pulse radars that use high pulse repetition frequencies, ambiguity in the measured distance can occur because the pulse repetition period corresponding to the high pulse repetition frequency is shorter than the delay time of the reflected wave signal. As a technique to eliminate ambiguity, multi-PRF ranging, which uses multiple types of pulse repetition frequencies, is known. The basic principle of multi-PRF ranging is disclosed in Non-Patent Document 1. Patent Document 1 discloses a ranging device that performs distance measurement using multi-PRF ranging.

[0004] The distance measuring device disclosed in Patent Document 1 has the function of transmitting a pulse train at a set pulse repetition period, acquiring a received pulse train generated when the pulse train is reflected by a target, and estimating the target location area based on the received pulse train. The distance measuring device estimates a new target location area by performing a correlation calculation between the target location area estimated based on the pulse train transmitted at a first pulse repetition period and the target location area estimated based on the pulse train transmitted at a second pulse repetition period different from the first pulse repetition period. If the new target location area is contained within a single region, the distance measuring device calculates the distance from the distance measuring device to the target as the distance from the distance measuring device to the target, and completes the distance measurement. If the new target location area is contained within multiple regions, the distance measuring device estimates the target location area based on a pulse train transmitted at a third pulse repetition period different from both the first and second pulse repetition periods, performs a correlation calculation between the new target location area and the previously estimated target location area, and estimates yet another new target location area.

[0005] As described above, the distance measuring device disclosed in Patent Document 1 can calculate the distance from the distance measuring device to the target as the distance to the target only if the new target existence region obtained by correlation calculation is contained within a single region. For this reason, the distance measuring device disclosed in Patent Document 1 has the problem that it is difficult to distinguish between multiple targets at close distances and difficult to detect multiple targets simultaneously.

[0006] The distance measuring device disclosed in Patent Document 2 solves the above-mentioned problems by using multiple types of pulse repetition periods to simultaneously detect multiple targets with high distance resolution.

[0007] The distance measuring device disclosed in Patent Document 2 estimates a new target location by performing a correlation calculation between a target location estimated based on a pulse train transmitted at a first pulse repetition period and a target location estimated based on a pulse train transmitted at a second pulse repetition period different from the first pulse repetition period. Based on multiple maximum peak values ​​appearing in the cumulative distribution in the correlation calculation, target information for multiple targets can be estimated. If the new target location is narrowed down to a number of target candidates, the distance measuring device calculates the distance from the device to the center of the new target location as the distance to the target and completes the distance measurement. If the new target location is not narrowed down to a number of target candidates, the distance measuring device estimates a target location based on a pulse train transmitted at a third pulse repetition period different from both the first and second pulse repetition periods, and performs a correlation calculation between the new target location and the previously estimated target location to estimate yet another new target location. As a result, the distance measuring device disclosed in Patent Document 2 can simultaneously detect multiple targets with high distance resolution. [Prior art documents] [Patent Documents]

[0008] [Patent Document 1] Japanese Patent Publication No. 2001-147266 [Patent Document 2] International Publication No. 2021 / 161504 [Non-patent literature]

[0009] [Non-Patent Document 1] Bassem R. Mahafza, “RADAR SIGNAL ANALYSIS AND PROCESSING USING MATLAB”, Chapman and Hall / CRC, pp. 416-418 (2009) [Overview of the Initiative] [Problems that the invention aims to solve]

[0010] The distance measuring device disclosed in Patent Document 2 estimates target information for multiple targets based on the maximum peak value appearing in the cumulative distribution. Although the distance measuring device disclosed in Patent Document 2 can detect multiple targets simultaneously, it has the problem that if the power of the received pulse train is weak, the target presence area cannot be obtained, which takes time to detect targets and increases the distance measuring time.

[0011] This disclosure is made in view of the above, and aims to provide a signal processor that can detect targets in a shorter time than conventional devices. [Means for solving the problem]

[0012] To solve the above-mentioned problems and achieve the objectives, the signal processor according to this disclosure is a signal processor that operates in cooperation with a sensor unit which generates a modulated pulse train at each of several types of pulse repetition periods, transmits the generated multiple modulated pulse trains to a search space, receives multiple reflected wave signals generated when one or more targets present in the search space reflect the multiple modulated pulse trains, and generates multiple received signals corresponding to each of several types of pulse repetition periods by applying signal processing to the multiple reflected wave signals, and has a pre-measurement unit which calculates multiple pre-measured values ​​representing the distance between the pulse radar system including the signal processor and one or more targets present in the search space based on the multiple received signals input from the sensor unit. The signal processor according to this disclosure further includes: a distance candidate generation unit that generates a plurality of ambiguity values ​​representing candidate distances between a pulse radar system and one or more targets from a plurality of pulse repetition periods, using the pulse repetition period corresponding to the pre-measured value from a plurality of types of pulse repetition periods for each of a plurality of pre-measured values; and a target presence distribution generation unit that generates a target presence distribution having a plurality of localization distributions indicating the likelihood that one or more targets exist in each of a plurality of regions centered on the plurality of ambiguity values, for each of a plurality of pre-measured values. The signal processor according to this disclosure further includes: an integration unit that calculates an integrated distribution by integrating the plurality of target presence distributions generated for each of the plurality of pre-measured values; a target detection unit that detects one or more maximum peak values ​​appearing in the integrated distribution and estimates target information relating to one or more targets based on the detected maximum peak values; and a transmission pulse selection unit. The target detection unit includes a peak detection unit that detects multiple maximum peak values ​​appearing in the cumulative distribution calculated by the cumulative unit, and a target information estimation unit that sorts the multiple maximum peak values ​​detected by the peak detection unit in descending or ascending order to generate an array of maximum peak values, and estimates the number of one or more targets as target information based on the maximum value of the array of absolute difference values ​​between adjacent maximum peak values ​​in the array of maximum peak values. The transmission pulse selection unit is, A predetermined number of pulse repetition period numbers n1 are selected from the range of 1 to Ni, and the pulse repetition period number n is replaced with the pulse repetition period number n corresponding to one of the selected pulse repetition period numbers n, where n is any integer from 1 to Ni. ru. [Effects of the Invention]

[0013] The signal processor described herein has the effect of being able to detect targets in a shorter time than conventional systems. [Brief explanation of the drawing]

[0014] [Figure 1] Block diagram showing the schematic configuration of the pulse radar system according to the embodiment. [Figure 2] A diagram conceptually representing a train of Ni modulated pulses generated with two different pulse repetition periods. [Figure 3] A graph conceptually representing examples of the waveforms of the modulated pulse train, reflected wave signal, received digital signal, and demodulated signal. [Figure 4] Graphs showing examples of a modulated pulse train and a reflected wave signal, respectively. [Figure 5] Graph showing an example of the target distribution [Figure 6] A schematic block diagram showing an example of the configuration of the target detection unit of the signal processor according to the embodiment. [Figure 7] A flowchart schematically shows some examples of the signal processing procedures performed by the signal processor according to the embodiment. [Figure 8] A flowchart schematically shows the remainder of an example of the signal processing procedure performed by the signal processor according to the embodiment. [Figure 9] A flowchart illustrating an example of the target information estimation process shown in Figure 8. [Figure 10] A flowchart illustrating an example of the convergence determination process shown in Figure 8. [Figure 11] A flowchart illustrating an example of the pulse width selection process shown in Figure 8. [Figure 12] A graph showing an example of an integrated distribution with eight maximum peak values. [Figure 13] Graph representing a descending order arrangement constructed based on the cumulative distribution shown in Figure 12. [Figure 14] Graph representing the array of absolute difference values ​​generated based on the descending order array shown in Figure 13. [Figure 15]This figure shows a processor in which at least some of the functions of the measurement control unit, pre-measurement unit, distance candidate generation unit, target presence distribution generation unit, integration unit, target detection unit, and transmission pulse selection unit of the signal processor according to the embodiment are realized by a processor. [Figure 16] This diagram shows a processing circuit in which at least some of the functions of the measurement control unit, pre-measurement unit, distance candidate generation unit, target presence distribution generation unit, integration unit, target detection unit, and transmission pulse selection unit of the signal processor according to the embodiment are realized by a processing circuit. [Modes for carrying out the invention]

[0015] The signal processor and pulse radar system according to the embodiment will be described in detail below with reference to the drawings.

[0016] Embodiment. Figure 1 is a block diagram illustrating the schematic configuration of a pulse radar system 1 according to an embodiment. As shown in Figure 1, the pulse radar system 1 includes a sensor unit 10 and a signal processor 20 that operates in conjunction with the sensor unit 10. The sensor unit 10 has the function of transmitting a modulated pulse train in a high-frequency band such as the microwave band or millimeter-wave band toward the search space, receiving a reflected wave signal generated when the modulated pulse train is reflected by one or more targets present in the search space, and generating a received signal corresponding to the modulated pulse train by applying signal processing to the reflected wave signal. More specifically, the sensor unit 10 generates a modulated pulse train for each of several types of pulse repetition periods, transmits the generated multiple modulated pulse trains toward the search space, receives multiple reflected wave signals generated when one or more targets present in the search space reflect multiple modulated pulse trains, and generates multiple received signals corresponding to each of several types of pulse repetition periods by applying signal processing to the multiple reflected wave signals. The above targets are not shown. The above received signals are received digital signals.

[0017] The sensor unit 10 has a signal generation circuit 11 that generates modulated pulse trains at each of several types of pulse repetition periods according to a control signal supplied from the signal processor 20. The signal generation circuit 11 generates multiple modulated pulse trains with different patterns corresponding to the multiple types of pulse repetition periods. The sensor unit 10 further has a transmit / receive switch 12 that switches the destination of the signal transmission. The sensor unit 10 further has an antenna 13 that transmits each modulated pulse train input from the signal generation circuit 11 via the transmit / receive switch 12 toward the search space, and a receiving circuit 14 that performs signal processing on the reflected wave signal input from the antenna 13 via the transmit / receive switch 12 to generate a received digital signal.

[0018] Antenna 13 transmits the modulated pulse Tx(n)(h,t) input from the signal generation circuit 11 via the transmit / receive switch 12 toward the search space. Figure 2 shows the repetition period T of Ni type pulses. pri (1), T pri (2), ···,T pri This diagram conceptually represents Ni modulation pulse trains TP(1), TP(2), ..., TP(Ni) generated by (Ni). Figure 2 shows Ni modulation pulse trains TP(1), TP(2), ..., TP(Ni) generated in sequence. Figure 2 also includes enlarged views of the first modulation pulse train TP(1), the second modulation pulse train TP(2), and the Nith modulation pulse train TP(Ni).

[0019] The nth modulated pulse train TP(n) has a nth pulse repetition period T pri It consists of a series of modulated pulses Tx(n)(0,t), Tx(n)(1,t), ..., Tx(n)(H-1,t) generated in (n). The pulse width of each of the multiple pulses contained in the nth modulated pulse train TP(n) is T0(n). As shown in Figure 2, each of the Ni modulated pulse trains TP(1), TP(2), ..., TP(Ni) has an observation period T obs and the period T allocated for signal processing sp Frame period T including frame A sensor unit 10 is provided, and for each observation period T obsEach modulated pulse train TP(n) is transmitted to [the specified location].

[0020] The receiving circuit 14 processes the reflected wave signal Rx(n)(t) input from the antenna 13 via the transmit / receive switch 12 to generate a received digital signal X(n)(m), and outputs the received digital signal X(n)(m) to the signal processor 20. The above received digital signal is the received video signal. The reflected wave signal Rx(n)(t) is a signal generated when the nth modulated pulse train TP(n) is reflected by one or more targets.

[0021] The signal processor 20 includes a measurement control unit 21, a pre-measurement unit 30, a distance candidate generation unit 34, a target presence distribution generation unit 35, an integration unit 36, a target detection unit 37, and a transmission pulse selection unit 38. The measurement control unit 21 has the function of supplying control signals to the sensor unit 10, and also has the function of controlling the operation of the pre-measurement unit 30, the distance candidate generation unit 34, the target presence distribution generation unit 35, the integration unit 36, and the target detection unit 37.

[0022] The measurement control unit 21 further has the function of receiving setting data specifying the range of the search space for searching for a target from an external device of the pulse radar system 1 via wired or wireless communication, and storing said setting data in memory. The external device of the pulse radar system 1 is not shown in the figure. The range of the search space is referred to as the "search range" below. The memory is not shown in the figure.

[0023] The pre-measurement unit 30 calculates a plurality of pre-measurement values ​​representing the distance between the pulse radar system 1 and one or more targets located within the search space, based on a plurality of received signals input from the sensor unit 10. The pre-measurement unit 30 includes a demodulation unit 31 and a distance measuring unit 32. The demodulation unit 31 performs pulse compression, i.e., demodulation processing, on the received digital signal X(n)(m) input from the sensor unit 10 to generate a demodulated signal F(n)(m).

[0024] When the demodulation unit 31 performs pulse compression based on the frequency modulation method, it can generate a demodulation signal F(n)(m) by performing a convolution operation between the reference signal Ex(m) and the received digital signal X(n)(m) in the time domain. The demodulation unit 31 can calculate a first frequency domain signal by performing a discrete Fourier transform on the received digital signal X(n)(m), calculate a second frequency domain signal by performing a discrete Fourier transform on the reference signal Ex(m), calculate a multiplication signal by multiplying the first frequency domain signal and the second frequency domain signal, and generate the demodulation signal F(n)(m) by performing an inverse discrete Fourier transform on the multiplication signal.

[0025] The ranging unit 32 detects the maximum peak value that appears in the time domain waveform of the demodulation signal F(n)(m), and calculates a preliminary measurement value T tgt (n) (i) representing the distance between the pulse radar system 1 and the target. i represents an integer within the range from 1 to N tgt assigned to the detected maximum peak value. N tgt is an integer representing the number of detected maximum peak values. The preliminary measurement value T tgt (n) (i) is a value indicating the round-trip propagation time of the radio wave corresponding to the distance between the pulse radar system 1 and the target. The preliminary measurement value T tgt (n) (i) may be calculated as a value indicating the distance between the pulse radar system 1 and the target.

[0026] FIG. 3 is a graph conceptually showing examples of the waveforms of the modulation pulse train TP(n), the reflected wave signal Rx(n)(t), the received digital signal X(n)(m), and the demodulation signal F(n)(m). In FIG. 3, (A) conceptually shows an example of the waveform of the modulation pulse train TP(n), (B) conceptually shows an example of the waveform of the reflected wave signal Rx(n)(t), (C) conceptually shows an example of the waveform of the received digital signal X(n)(m), and (D) conceptually shows an example of the waveform of the demodulation signal F(n)(m). In each of (A) to (D) of FIG. 3, the horizontal axis indicates time, and the vertical axis indicates the amplitude of the signal.

[0027] The reflected wave signal Rx(n)(t) shown in Figure 3(B) is the reflected wave signal component Rx1 generated when the transmitted modulated pulse train TP(n) is reflected by two targets. (n) (t) and reflected wave signal component Rx2 (n) (t) is included. The received digital signal X(n)(m) shown in Figure 3(C) has a reflected wave signal component Rx1 (n) (t) Received digital signal component X1 (n) (m) and the reflected wave signal component Rx2 (n) (t) Received digital signal component X2 (n) (m) is included. The demodulated signal F(n)(m) shown in Figure 3(D) is the received digital signal component X1 (n) (m) corresponds to the demodulated signal component D1 and the received digital signal component X2 (n) It includes the demodulated signal component D2 corresponding to (m). The demodulated signal component is a compressed pulse. Δt shown in Figures 3(C) and 3(D) is the sampling interval of the received digital signal component Xq(n)(m). Xq(n)(m) is the received digital signal component relating to the q-th target, m is an integer in the range of 0 to M-1 representing the sampling number, and M is the sampling number. The distance measuring unit 32 determines a pre-measured value T based on the maximum peak values ​​appearing in the time-domain waveforms of demodulated signal component D1 and demodulated signal component D2. tgt (n) (1) and pre-measured value T tgt (n) (2) can be calculated.

[0028] However, the pre-measured value T tgt (n) (i) is not necessarily a value that uniquely represents the distance between the pulse radar system 1 and the target. This is because the pulse repetition period T pri Ambiguity occurs when (n) is shorter than the delay time of the reflected wave signal component. The above delay time is the round-trip propagation time of the radio waves between antenna 13 and the target. This point will be explained below with reference to Figure 4.

[0029] Figure 4 is a graph showing examples of a modulated pulse train TP(n) and a reflected wave signal Rx(n)(t), each consisting of a series of modulated pulses. In Figure 4, (A) conceptually represents an example of a modulated pulse train TP(n) consisting of a series of modulated pulses, and (B) represents an example of a reflected wave signal Rx(n)(t). In both (A) and (B) of Figure 4, the horizontal axis represents time, and the vertical axis represents the amplitude of the signal. As shown in Figure 4(B), the reflected wave signal Rx(n)(t) corresponds to the reflected wave signal component Rx of the modulated pulse train TP(n) in Figure 4(A). i This includes the pulse repetition period T. pri Since (n) is short, the reflected wave signal component Rx i An ambiguity exists in that it is not clear from which of the series of modulation pulses T originated. In Figure 4, T nrm (n) (i) is the pre-measured value T, as shown in equation (1) below. tgt (n) (i) Repeat pulse with period T pri This is a normalized pre-measured value normalized by (n). n is an integer from 1 to Ni. i is from 1 to N tgt It is any integer up to 1.

[0030]

number

[0031] In the examples of Figures 4(A) and 4(B), the following three values ​​can be considered as ambiguity values ​​representing candidate distances to targets in the search space, corresponding to the three modulation pulses in the modulation pulse train TP(n). c is the speed of light. (T nrm (n) (i) + 0) × T pri (n) × (c / 2), (T nrm (n) (i) + 1) × T pri (n) × (c / 2), (T nrm (n) (i) + 2) × Tpri (n) × (c / 2).

[0032] For a non-zero integer K, R is an ambiguity value representing candidate distances to a target existing in the search space. i (n) When represented by (K), the ambiguity value R i (n) (K) can be expressed by the following equation (2), where n is an integer from 1 to Ni, and i is an integer from 1 to N. tgt It is any integer up to 1.

[0033]

number

[0034] The distance candidate generation unit 34 generates multiple ambiguity values ​​representing candidate distances between the pulse radar system 1 and one or more targets from the pre-measured values, using the pulse repetition period corresponding to the pre-measured value from among multiple types of pulse repetition periods. Furthermore, the distance candidate generation unit 34 generates multiple ambiguity values ​​representing candidate distances between the pulse radar system 1 and one or more targets from the pre-measured values, using the pulse repetition period T pri Using (n), multiple pre-measured values ​​T tgt (n) From each of (i), a number of ambiguity values ​​R representing candidate distances between the pulse radar system 1 and the target. i (n) (K min (n) ), R i (n) (K min (n) +1),···,R i (n) (K max (n) ) generates K min (n) The nearest proximity distance R within the search range specified by the measurement control unit 21 is the nearest proximity distance R min This is the corresponding lower limit. K max (n) The furthest distance R within the search range is max This is the corresponding upper limit.

[0035] The target existence distribution generation unit 35 generates a target existence distribution having a plurality of localization distributions indicating the probability that one or more targets will exist in each of a plurality of regions centered on a plurality of ambiguity values for each of the plurality of pre-measurement values. More specifically, the target existence distribution generation unit 35 generates a plurality of pre-measurement values T tgt (n) (i) for each of the plurality of ambiguity values R i (n) (K min (n) ), ···, R i (n) (K max (n) ) generates a target existence distribution P i (n) (r) having a plurality of localization distributions in each of the plurality of regions centered on each of them. r is a value representing a distance. Each localization distribution is a local target existence distribution indicating the probability that a target will exist in a local region centered on each ambiguity value R i (n) (K). For example, the target existence distribution P i (n) (r) can be expressed as a linear combination of the localization distributions F(R i (n) (K); r) as shown in the following formula (3).

[0036]

Equation

[0037] FIG. 5 is a graph showing an example of the target existence distribution P i (n) (r). More specifically, (A)-(C) in FIG. 5 represent examples of the target existence distribution P i <00所00097>(r). FIG. 5(A) shows the target existence distribution P1 (1) (r) when i and n are 1. FIG. 5(B) shows the target existence distribution P1 (2) (r) when i is 1 and n is 2. FIG. 5(C) shows the target existence distribution P1 (3)(r) is shown. The target presence distribution P is shown in Figure 5. i (n) (r) is a set of multiple localized distributions F(R i (n) It is composed of combinations of (K);r). K is K min (n) ,K min (n) +1,···,K max (n) -1,K max (n) Figure 5(D) shows the target abundance distribution P1. (1) (r), target existence distribution P1 (2) (r) and target distribution P1 (3) This graph represents the integrated distribution Φ(r) obtained by accumulating (r). The integrated distribution Φ(r) shown in Figure 5(D) represents the distance r from the true target. p (1) has a single maximum peak value.

[0038] The integration unit 36 ​​calculates the integrated distribution by integrating the multiple target existence distributions generated for each of the multiple pre-measured values. More specifically, the integration unit 36 ​​calculates the target existence distribution P generated by the target existence distribution generation unit 35. i (n) The integrated distribution Φ(r) is calculated by integrating (r) over the PRI number n and identification number i. PRI is the pulse repetition period. The integrated distribution Φ(r) is shown in Figure 5 (D). In the integrated distribution Φ(r), it is expected that low values ​​will appear for the distance to the false target, and a sharp maximum peak value will appear for the distance to the true target.

[0039] The target detection unit 37 detects one or more maximum peak values ​​appearing in the cumulative distribution and estimates target information for one or more targets based on the detected maximum peak values. The target detection unit 37 may estimate the number of one or more targets as target information multiple times. Figure 6 is a schematic block diagram showing an example of the configuration of the target detection unit 37 in the signal processor 20 according to the embodiment. As shown in Figure 6, the target detection unit 37 has a peak detection unit 41 that detects one or more maximum peak values ​​exceeding a predetermined peak detection threshold Th from the cumulative distribution Φ(r). More specifically, the peak detection unit 41 detects one or more maximum peak values ​​appearing in the cumulative distribution calculated by the cumulative unit 36.

[0040] The target detection unit 37 further includes a target information estimation unit 42 that estimates target information based on one or more maximum peak values ​​detected by the peak detection unit 41. More specifically, the target information estimation unit 42 sorts the multiple maximum peak values ​​detected by the peak detection unit 41 in descending or ascending order to generate an array of maximum peak values, and estimates the number of one or more targets as target information based on the maximum value of the array of absolute difference values ​​between adjacent maximum peak values ​​in the array of maximum peak values. The above target information is, for example, information indicating the distance between the pulse radar system 1 and the target and the number of targets. The target detection unit 37 further includes a determination unit 43 that determines whether the target information estimated by the target information estimation unit 42 satisfies predetermined convergence conditions.

[0041] If the number of targets has been estimated multiple times, the determination unit 43 determines that the convergence condition has been met when a statistic representing the variability of the estimated number of targets is within a predetermined tolerance range, and determines that the convergence condition has not been met when the statistic is outside the tolerance range. The above statistic is, for example, the variance or the standard deviation. If the determination unit 43 determines that the target information estimated by the target information estimation unit 42 satisfies the convergence condition, it outputs the estimated target information to an external device 39 such as a display. The external device 39 is not limited to a display. The external device 39 may be a tracking device that tracks targets. Figure 6 also shows an external device 39.

[0042] The determination unit 43 supplies determination data indicating the determination result to the measurement control unit 21. The measurement control unit 21 uses the determination data to determine whether or not to repeat the signal processing. Figure 6 also shows the signal generation circuit 11, the measurement control unit 21, the integration unit 36, and the transmission pulse selection unit 38.

[0043] The transmission pulse selection unit 38 selects a modulation pulse train that does not result in a transmission eclipse at at least one target distance candidate, based on the target information estimated by the target information estimation unit 42 of the target detection unit 37.

[0044] Next, the signal processing procedures performed by the signal processor 20 will be described with reference to Figures 7 to 11. Figure 7 is a flowchart schematically showing a part of the signal processing procedures performed by the signal processor 20 according to the embodiment. Figure 8 is a flowchart schematically showing the remaining part of the signal processing procedures performed by the signal processor 20 according to the embodiment. The flowchart in Figure 7 and the flowchart in Figure 8 are connected via connectors C1, C2, and C3. Figure 9 is a flowchart schematically showing an example of the target information estimation procedure in step S16 shown in Figure 8. Figure 10 is a flowchart schematically showing an example of the convergence determination procedure in step S17 shown in Figure 8. Figure 11 is a flowchart schematically showing an example of the pulse width selection procedure in step S21 shown in Figure 8.

[0045] When a search command is received from an external device (not shown), the measurement control unit 21 sets up multiple types of pulse repetition periods T corresponding to each of the multiple types of pulse repetition frequencies. pri (1) ~ T pri (Ni) is set (S1). At this time, the measurement control unit 21 sets the pulse repetition period T pri (1) ~ T pri (Ni) can be set to different initial values. Next, the measurement control unit 21 initializes the value of PRI number n to zero (S2). PRI is the pulse repetition period.

[0046] Next, the measurement control unit 21 cyclically increments the PRI number n within the range from 1 to Ni (S3). That is, in step S3, if the increment value obtained by increasing the PRI number n by 1, i.e., "n+1", is within the range from 1 to Ni, the measurement control unit 21 replaces the value of the PRI number n with that increment value, and if that increment value exceeds Ni, it replaces the value of the PRI number n with 1.

[0047] Next, the measurement control unit 21 controls the sensor unit 10 to control the pulse repetition period T pri At (n), the corresponding modulated pulse train TP(n) is transmitted from antenna 13 (S4). At this time, antenna 13 transmits the modulated pulse train TP(n), which is input from the signal generation circuit 11 via the transmit / receive switch 12, toward the search space. The receiving circuit 14 performs signal processing on the reflected wave signal Rx(n)(t) input from antenna 13 via the transmit / receive switch 12 to generate a received digital signal X(n)(m), and outputs the received digital signal X(n)(m) to the signal processor 20. As described above, the received digital signal is the received video signal.

[0048] When the signal processor 20 acquires the received digital signal X(n)(m) from the sensor unit 10 (S5), the demodulation unit 31 in the pre-measurement unit 30 applies pulse compression, i.e., demodulation processing, to the received digital signal X(n)(m) to generate a demodulated signal F(n)(m) (S6).

[0049] The distance measuring unit 32 in the pre-measurement unit 30 determines whether the amplitude of the demodulated signal F(n)(m) is greater than a predetermined threshold (S7). If the distance measuring unit 32 determines that the amplitude of the demodulated signal F(n)(m) is less than or equal to the predetermined threshold (No in S7), the distance measuring unit 32 then determines the less reliable pre-measurement value T. tgt (n) To avoid the calculation of (i), the action in step S3 is performed.

[0050] If the distance measuring unit 32 determines that the amplitude of the demodulated signal F(n)(m) is greater than a predetermined threshold (Yes in S7), it calculates one or more pre-measured values ​​T based on the demodulated signal F(n)(m). tgt (n) (i) is attempted to be calculated (S8). The distance measuring unit 32 measures the pre-measured value T. tgt (n) If the calculation of (i) is unsuccessful (No in S9), the operation in step S3 is performed.

[0051] The distance measuring unit 32 sets the pre-measured value T tgt (n) If the calculation of (i) is successful (Yes in S9), the distance candidate generation unit 34 generates each pre-measured value T tgt (n) (i) That is, for each combination of PRI number n and identification number i, the pulse repetition period T pri Using (n), each pre-measured value T tgt (n) (i) Multiple ambiguity values ​​R i (n) (K min (n) ), R i (n) (K min (n) +1),···,R i (n) (K max (n) (S10) generates ).

[0052] Next, the target presence distribution generation unit 35 generates each pre-measured value T tgt (n) (i) The ambiguity value R i (n) (K min (n) ),···,R i (n) (K max (n) Target existence distribution P has multiple localized distributions in each of the multiple regions centered around ). i (n) (r) is generated (S11). Multiple target existence distributions P corresponding to each of the multiple PRI numbers n. i (n)If (r) exists (Yes in S12), the integrating unit 36 ​​calculates the target existence distribution P i (n) The integrated distribution Φ(r) is calculated by integrating (r) over the PRI number n and identification number i (S13). Multiple target existence distributions P corresponding to each of the multiple PRI numbers n. i (n) If (r) does not yet exist (No in S12), the operation in step S3 is performed.

[0053] After the operation in step S13 is performed, the peak detection unit 41 shown in Figure 6 attempts to detect the maximum peak value appearing in the integration distribution Φ(r) (S14). As described above, the peak detection unit 41 has the function of detecting multiple maximum peak values ​​from the integration distribution Φ(r) that exceed a predetermined peak detection threshold Th. The peak detection threshold Th is set to a value that can detect not only the maximum peak value corresponding to the true target but also the maximum peak value corresponding to the false target. If the peak detection unit 41 does not succeed in detecting the maximum peak value appearing in the integration distribution Φ(r) (No in S15), the operation in step S3 is performed. If the peak detection unit 41 succeeds in detecting the maximum peak value appearing in the integration distribution Φ(r) (Yes in S15), the target information estimation unit 42 shown in Figure 6 performs a target information estimation process that estimates the distance between the pulse radar system 1 and the true target and the number of targets as target information based on the one or more maximum peak values ​​detected by the peak detection unit 41 (S16). In the target information estimation process of step S16, multiple target distance candidates are estimated.

[0054] As described above, Figure 9 is a flowchart that schematically shows an example of the procedure for the target information estimation process in step S16 shown in Figure 8. The target information estimation unit 42 sorts the multiple maximum peak values ​​detected by the peak detection unit 41 in descending or ascending order to generate a descending array Π or ascending array Ψ of maximum peak values ​​(S31). Next, the target information estimation unit 42 generates an array of absolute difference values ​​between adjacent maximum peak values ​​(S32). Next, the target information estimation unit 42 detects the maximum value from the array of absolute difference values ​​(S33). Finally, the target information estimation unit 42 estimates the number of targets and the distance between the pulse radar system 1 and the targets based on the maximum value (S34).

[0055] Figure 12 shows the eight maximum peak values ​​Φ(r p (1)),Φ(r p (2)),···,Φ(r p (8)) is a graph showing an example of an integrated distribution Φ(r). Figure 12 is a graph showing an example of an integrated distribution Φ(r) with multiple local peak values. In the example in Figure 12, the integrated distribution Φ(r) is the distance r from the true target. p (1), r p (2) has two maximum peak values. Figure 13 is a graph representing the descending sequence Π constructed based on the cumulative distribution Φ(r) shown in Figure 12. As shown in Figure 13, the descending sequence Π consists of a group of maximum peak values ​​80R corresponding to the true target and a group of maximum peak values ​​80E corresponding to the false target. It can be seen that the difference between the maximum peak values ​​corresponding to the true target is relatively small, the difference between the maximum peak values ​​corresponding to the false target is also relatively small, and the difference between the maximum peak value corresponding to the true target and the maximum peak value corresponding to the false target is relatively large. Figure 14 is a graph representing the sequence of difference absolute values ​​Δ(u) generated based on the descending sequence Π shown in Figure 13. As shown in Figures 13 and 14, the sequence number 2, which corresponds to the maximum value Δ(2), coincides with the number of true targets.

[0056] Next, the determination unit 43 shown in Figure 6 performs a convergence determination process using the target information estimated by the target information estimation unit 42 (S17). At this time, the determination unit 43 determines that the convergence condition has been met if the estimated number of targets satisfies the predetermined convergence condition, and determines that the convergence condition has not been met otherwise. The determination unit 43 supplies determination data indicating the determination result to the measurement control unit 21.

[0057] As described above, Figure 10 is a flowchart that schematically shows an example of the convergence determination process procedure in step S17 shown in Figure 8. The determination unit 43 determines whether the estimation of the target number in step S16 has been performed more than a predetermined number of times (S41). If the determination unit 43 determines that the estimation of the target number has been performed more than a predetermined number of times (Yes in S41), it calculates a statistic that represents the variability of the target number estimated over multiple times (S42). For example, the statistic may be the variance or the standard deviation.

[0058] The determination unit 43 determines whether the calculated statistic is within an acceptable range (S43). If the determination unit 43 determines that the calculated statistic is within an acceptable range (Yes in S43), it determines that the convergence condition has been met (S44). If the determination unit 43 determines that the calculated statistic is not within an acceptable range (No in S43), it determines that the convergence condition has not been met (S45). The determination unit 43 also determines that the convergence condition has not been met if it determines that the estimation of the target number has not been performed more than a predetermined number of times (No in S41) (S45).

[0059] If the determination unit 43 determines that the convergence condition has been met in the convergence determination process of step S17 (Yes in S18), it outputs the target information estimated in step S16 to an external device 39 such as a display (S19). The measurement control unit 21 completes the signal processing.

[0060] If the determination unit 43 determines that the convergence condition is not met in the convergence determination process of step S17 (No in S18), and the top N of the single or multiple maximum peak values ​​are greater than a predetermined value, that is, the number of target distance candidates is greater than a predetermined number N (No in S20), the measurement control unit 21 controls the pre-measurement unit 30, the distance candidate generation unit 34, the target presence distribution generation unit 35, the integration unit 36, and the target detection unit 37 to execute the operations from step S3 onwards again.

[0061] If the determination unit 43 determines that the convergence conditions are not met in the convergence determination process of step S17 (No in S18), and the top N of the single or multiple maximum peak values ​​are less than or equal to a predetermined value, that is, the number of target distance candidates is less than or equal to a predetermined number N (Yes in S20), the transmission pulse selection unit 38 executes the pulse width selection process (S21).

[0062] As described above, Figure 11 is a flowchart that schematically shows an example of the pulse width selection process procedure in step S21 shown in Figure 8. The transmit pulse selection unit 38 selects a predetermined number x of PRI numbers n1 from the range from 1 to Ni that do not result in a transmit eclipse for at least one of the multiple target distance candidates estimated in the target information estimation process in step S16 (S51). The transmit pulse selection unit 38 replaces PRI number n with PRI number n1 corresponding to one of the selected x (S52). The measurement control unit 21 controls the pre-measurement unit 30, distance candidate generation unit 34, target presence distribution generation unit 35, integration unit 36, and target detection unit 37 to execute the operations from step S4 onwards again.

[0063] As described above, in the signal processor 20 according to the embodiment, the distance candidate generation unit 34 has a pulse repetition period T pri (n) is used to calculate each pre-measurement value T by the pre-measurement unit 30. tgt (n) (i) Multiple ambiguity values ​​R i (n) (K min (n) ), R i(n) (K min (n) +1),···,R i (n) (K max (n) The target presence distribution generation unit 35 generates each pre-measured value T. tgt (n) (i) Multiple ambiguity values ​​R i (n) (K min (n) ), R i (n) (K min (n) +1),···,R i (n) (K max (n) Target existence distribution P has multiple localized distributions in each of the multiple regions centered around ). i (n) (r) is generated. Each of the multiple regions is a distribution that indicates the probability that one or more targets will exist. The integration unit 36 ​​generates the target existence distribution P i (n) The integrated distribution Φ(r) is calculated by integrating (r). When multiple targets exist within the search space, as shown in Figure 12, multiple maximum peak values ​​corresponding to each of the multiple targets appear in the integrated distribution Φ(r). The target detection unit 37 can detect the multiple maximum peak values ​​appearing in the integrated distribution Φ(r) and estimate target information based on the detected maximum peak values. The target information is information indicating the distance between the pulse radar system 1 and the target, and the number of targets. When the number of target candidates has been narrowed down to multiple, the transmission pulse selection unit 38 supplies each modulated pulse train information that does not become a transmission eclipse at least one distance candidate to the signal generation circuit 11. Therefore, the signal processor 20 according to this embodiment can detect targets existing within the search space with high distance resolution, can select the number of target candidates in a shorter time than conventionally, and complete signal processing. In other words, the signal processor 20 can detect targets in a shorter time than conventionally.

[0064] Furthermore, the signal processor 20 according to this embodiment can estimate target information in a shorter time and with higher accuracy than conventional methods by selectively transmitting a modulated pulse train that does not become a transmission eclipse at at least one of the single or multiple target distance candidates, based on the single or multiple maximum peak values ​​appearing in the cumulative distribution.

[0065] Each time the digital signal X(n)(m) is input from the sensor unit 10 to the signal processor 20, the target detection unit 37 estimates the number of targets if the conditions are met, that is, if Yes in steps S7, S9, S12, and S15 in Figure 7, and can determine whether the estimated number of targets satisfies predetermined convergence conditions (S16 and S17 in Figure 8). Based on the determination data indicating the result of the determination made by the target detection unit 37, the measurement control unit 21 can accurately determine the timing to exit the repeated operation from steps S3 to S16 in Figures 7 and 8 and complete the signal processing.

[0066] Figure 15 shows a processor 91 in which at least some of the functions of the measurement control unit 21, pre-measurement unit 30, distance candidate generation unit 34, target presence distribution generation unit 35, integration unit 36, target detection unit 37, and transmission pulse selection unit 38 of the signal processor 20 according to the embodiment are realized by the processor 91. In other words, at least some of the functions of the measurement control unit 21, pre-measurement unit 30, distance candidate generation unit 34, target presence distribution generation unit 35, integration unit 36, target detection unit 37, and transmission pulse selection unit 38 may be realized by a processor 91 that executes a program stored in memory 92. The processor 91 is a CPU (Central Processing Unit), processing system, arithmetic system, microprocessor, or DSP (Digital Signal Processor). The memory 92 is also shown in Figure 15.

[0067] When at least some of the functions of the measurement control unit 21, pre-measurement unit 30, distance candidate generation unit 34, target presence distribution generation unit 35, integration unit 36, target detection unit 37, and transmission pulse selection unit 38 are implemented by the processor 91, at least some of these functions are implemented by the processor 91 and software, firmware, or a combination of software and firmware. The software or firmware is written as a program and stored in memory 92. The processor 91 implements at least some of the functions of the measurement control unit 21, pre-measurement unit 30, distance candidate generation unit 34, target presence distribution generation unit 35, integration unit 36, target detection unit 37, and transmission pulse selection unit 38 by reading and executing the program stored in memory 92.

[0068] When at least some of the functions of the measurement control unit 21, pre-measurement unit 30, distance candidate generation unit 34, target presence distribution generation unit 35, integration unit 36, target detection unit 37, and transmission pulse selection unit 38 are implemented by the processor 91, the signal processor 20 has a memory 92 for storing a program in which at least some of the steps performed by the measurement control unit 21, pre-measurement unit 30, distance candidate generation unit 34, target presence distribution generation unit 35, integration unit 36, target detection unit 37, and transmission pulse selection unit 38 are consequently executed. The program stored in the memory 92 can also be said to cause the computer to execute at least some of the procedures or methods performed by the measurement control unit 21, pre-measurement unit 30, distance candidate generation unit 34, target presence distribution generation unit 35, integration unit 36, target detection unit 37, and transmission pulse selection unit 38.

[0069] Memory 92 includes, for example, non-volatile or volatile semiconductor memory such as RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable Read Only Memory), EEPROM (Registered Trademark) (Electrically Erasable Programmable Read-Only Memory), magnetic disks, flexible disks, optical disks, compact disks, minidiscs, or DVDs (Digital Versatile Disks).

[0070] Figure 16 shows a processing circuit 93 in which at least some of the functions of the measurement control unit 21, pre-measurement unit 30, distance candidate generation unit 34, target presence distribution generation unit 35, integration unit 36, target detection unit 37, and transmission pulse selection unit 38 of the signal processor 20 according to the embodiment are realized by the processing circuit 93. In other words, at least some of the functions of the measurement control unit 21, pre-measurement unit 30, distance candidate generation unit 34, target presence distribution generation unit 35, integration unit 36, target detection unit 37, and transmission pulse selection unit 38 may be realized by the processing circuit 93.

[0071] The processing circuit 93 is dedicated hardware. The processing circuit 93 may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or a combination thereof.

[0072] Some functions of the measurement control unit 21, pre-measurement unit 30, distance candidate generation unit 34, target presence distribution generation unit 35, integration unit 36, target detection unit 37, and transmission pulse selection unit 38 may be implemented by separate dedicated hardware from the hardware that implements the remaining functions of the measurement control unit 21, pre-measurement unit 30, distance candidate generation unit 34, target presence distribution generation unit 35, integration unit 36, target detection unit 37, and transmission pulse selection unit 38.

[0073] Regarding the multiple functions of the measurement control unit 21, pre-measurement unit 30, distance candidate generation unit 34, target presence distribution generation unit 35, integration unit 36, target detection unit 37, and transmission pulse selection unit 38, some of these functions may be implemented by software or firmware, while the remaining functions may be implemented by dedicated hardware. In this way, the multiple functions of the measurement control unit 21, pre-measurement unit 30, distance candidate generation unit 34, target presence distribution generation unit 35, integration unit 36, target detection unit 37, and transmission pulse selection unit 38 can be implemented by hardware, software, firmware, or a combination thereof.

[0074] At least some of the functions of the signal generation circuit 11, the transmit / receive switch 12, and the receiving circuit 14 of the sensor unit 10 of the pulse radar system 1 according to this embodiment may be implemented by a processor that executes a program stored in memory, or by a processing circuit. The memory is equivalent to memory 92, the processor is equivalent to processor 91, and the processing circuit is equivalent to processing circuit 93.

[0075] The configurations shown in the above embodiments are examples only, and can be combined with other known technologies, and parts of the configuration can be omitted or modified without departing from the gist of the invention. [Explanation of Symbols]

[0076] 1 Pulse radar system, 10 Sensor unit, 11 Signal generation circuit, 12 Transmit / receive switch, 13 Antenna, 14 Receiving circuit, 20 Signal processor, 21 Measurement control unit, 30 Pre-measurement unit, 31 Demodulation unit, 32 Distance measurement unit, 34 Distance candidate generation unit, 35 Target presence distribution generation unit, 36 Integration unit, 37 Target detection unit, 38 Transmit pulse selection unit, 39 External device, 41 Peak detection unit, 42 Target information estimation unit, 43 Judgment unit, 80E Maximum peak value group corresponding to false targets, 80R Maximum peak value group corresponding to true targets, 91 Processor, 92 Memory, 93 Processing circuit.

Claims

1. A signal processor that operates in conjunction with a sensor unit, which generates a modulated pulse train at each of several types of pulse repetition periods, transmits the generated multiple modulated pulse trains to a search space, receives multiple reflected wave signals generated when one or more targets present in the search space reflect the multiple modulated pulse trains, and generates multiple received signals corresponding to each of the several types of pulse repetition periods by applying signal processing to the multiple reflected wave signals, A pre-measurement unit calculates a plurality of pre-measured values ​​representing the distance between the pulse radar system, which includes the signal processor, and the one or more targets located within the search space, based on a plurality of received signals input from the sensor unit. A distance candidate generation unit generates a plurality of ambiguity values ​​representing candidate distances between the pulse radar system and the one or more targets from the pre-measured values, using the pulse repetition period corresponding to the pre-measured value among the plurality of pulse repetition periods. A target existence distribution generation unit generates a target existence distribution having a plurality of localization distributions that indicate the likelihood that one or more targets exist in each of the plurality of regions centered on the plurality of ambiguity values, for each of the plurality of pre-measured values. An integration unit calculates an integrated distribution by integrating a plurality of target existence distributions generated for each of the plurality of pre-measured values, A target detection unit detects one or more maximum peak values ​​appearing in the cumulative distribution and estimates target information for the one or more targets based on the detected maximum peak values. It includes a transmission pulse selection unit, The target detection unit, A peak detection unit detects multiple maximum peak values ​​that appear in the integrated distribution calculated by the integration unit, The system includes a target information estimation unit that sorts the plurality of maximum peak values ​​detected by the peak detection unit in descending or ascending order to generate an array of maximum peak values, and estimates the number of one or more targets as target information based on the maximum value of the array of absolute difference values ​​between adjacent maximum peak values ​​in the array of maximum peak values, The transmission pulse selection unit selects a predetermined number of multiple pulse repetition period numbers n1 from the range of 1 to Ni, and replaces the pulse repetition period number n with the pulse repetition period n1 corresponding to one of the selected numbers, where n is an integer from 1 to Ni. A signal processor characterized by the following features.

2. The target detection unit estimates the number of one or more targets as target information over multiple cycles. The signal processor according to feature 1.

3. A signal processor according to claim 1 or 2, The sensor unit and A pulse radar system characterized by comprising the following features.

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