JP2013029402A - Radar device and reception data processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a radar device capable of accurately integrating data estimated on the basis of a past scan result into data obtained by current scan, and a reception data processing method used for the radar device.SOLUTION: A radar device includes a radio part, a pulse compression part, a Doppler filter processing part, a signal processing part, a prediction part, an addition part, and an extraction part. The pulse compression part performs pulse compression processing to a pulse signal received by the radio part. The Doppler filter processing part generates range cell data for every frequency bin by performing Doppler filter processing on the data after the pulse compression. The signal processing part converts the range cell data into intrinsic data. The prediction part generates prediction data predicting that a target is positioned within a predetermined range on the basis of a last scan result. The addition part sums up the prediction data and intrinsic data obtained in next scan at the same position. The extraction part extracts data at a position of maximum intensity from among the summed-up data.

Description

  Embodiments described herein relate generally to a radar apparatus that searches for a target by receiving a pulse signal in which a transmission pulse is reflected, scattered, or diffracted, and a received data processing method used in the radar apparatus.

  The radar apparatus receives a pulse signal in which a plurality of transmission pulses transmitted at a constant PRI (Pulse Repetition Interval) are reflected, scattered or diffracted. The radar apparatus performs coherent integration on the received pulse signal. Here, coherent integration is a process of coherently integrating a plurality of pulse signals in the same range. As described above, a period during which coherent integration is performed on the pulse signal received by the radar apparatus is generally referred to as CPI (Coherent Processing Interval). Then, the radar apparatus incoherently integrates data acquired by coherent integration with data estimated based on past scan results, and measures the intensity thereof. When the measured intensity exceeds a predetermined threshold value, the radar apparatus detects that a target exists in this range bin.

  However, in this type of radar apparatus, when estimating the amount of movement of the target between scans based on the past scan results, an error occurs in the estimated value of the amount of movement of the target, so that incoherent integration may not be performed accurately. is there.

E. Fisher, A. H. Heimovich, "Spatial diversity in radar-models and detection Performance", IEEE Trans. On Signal Processing, vol. 54, no. 3, pp. 823-838 E. Fisher, A. H. Heimovich, "Performance of MIMO Radar System: Advantages of Angular Diversity", IEEE Trans. On Signal Processing, 2004

  As described above, in the above radar apparatus, an error occurs in the target range estimation information that moves between scans, and thus acquired data may not be accurately integrated.

  Accordingly, an object of the present invention is to provide a radar device capable of accurately integrating data estimated based on past scan results with data obtained in the current scan, and a received data processing method used in the radar device. It is in.

  According to the embodiment, the radar apparatus includes a radio unit, a pulse compression unit, a Doppler filter processing unit, a signal processing unit, a prediction unit, an addition unit, and an extraction unit. The radio unit receives a pulse signal. The pulse compression unit performs pulse compression processing on the pulse signal to generate range cell data for each pulse signal. The Doppler filter processing unit performs Doppler filter processing on the range cell data from the pulse compression unit, thereby generating range cell data for each frequency bin. The signal processing unit converts the range cell data acquired for each scan by the Doppler filter processing unit into specific data specified by parameters including a target position and velocity. The prediction unit creates prediction data in which the target is predicted to be located within a preset range from the position predicted based on the target position and speed obtained from the previous scan result. The adding unit adds the prediction data and the unique data acquired at the next scan at the same position. The extraction unit extracts data at the position having the maximum intensity from the data added at the same position, and outputs the extracted data to the prediction unit and the subsequent stage as a scan result.

It is a block diagram which shows the function structure of the radar apparatus which concerns on 1st Embodiment. It is a figure which shows the pulse compression process by the pulse compression part of FIG. It is a figure which shows the coherent integration by the Doppler filter process part of FIG. It is a figure which shows the parameter of the four-dimensional data which the signal processing part of FIG. 1 produces. It is a figure which shows the sequence at the time of the integration part and prediction part of FIG. 1 producing integral four-dimensional data. It is a figure which shows the integration four-dimensional data produced by the integration process shown in FIG. It is a figure which shows the simulation item used by simulation about the radar apparatus of FIG. It is a figure which shows the simulation result at the time of using the simulation item of FIG. It is a figure which shows the simulation result which shows the maximum detection distance of the radar apparatus of FIG. 1, and the conventional radar apparatus. It is a block diagram which shows the structure of the MIMO radar system in which the radar apparatus which concerns on 2nd Embodiment is included. It is a block diagram which shows the function structure of the radar apparatus of FIG.

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

(First embodiment)
FIG. 1 is a block diagram illustrating a functional configuration of the radar apparatus according to the first embodiment. The radar apparatus shown in FIG. 1 includes a radio unit 10, a spatial processing unit 20, a pulse compression unit 30, a Doppler filter processing unit 40, a signal processing unit 50, an integration unit 60, a prediction unit 70, and a recording unit 80.

  The radio unit 10 includes an antenna element 11, a reception module 12, a frequency conversion unit 13, and an analog-digital conversion unit 14.

  The antenna element 11 receives a pulse signal in which a plurality of transmission pulses transmitted at a constant PRI (Pulse Repetition Interval) are reflected, scattered or diffracted. At this time, it is assumed that M transmission pulses are transmitted at 1 CPI (Coherent Processing Interval), and the antenna element 11 receives M pulse signals. The antenna element 11 outputs the received pulse signal to the reception module 12. The receiving module 12 amplifies the power of the pulse signal from the antenna element 11. The frequency converter 13 converts the pulse signal amplified by the receiving module 12 into a baseband. The analog-digital conversion unit 14 digitally converts the pulse signal from the frequency conversion unit 13 and outputs the digital signal to the spatial processing unit 20.

  The spatial processing unit 20 forms a reception beam by superimposing a predetermined beam weight on the signal digitized by the radio unit 10.

  The pulse compression unit 30 performs pulse compression processing on the signal from the spatial processing unit 20 and generates range cell data for each pulse signal. FIG. 2 is a diagram schematically illustrating the pulse compression processing by the pulse compression unit 30.

  The Doppler filter processing unit 40 performs coherent integration on every M range cell data from the pulse compression unit 30. In other words, the Doppler filter processing unit 40 generates the range cell data for each of the M frequency bins by performing FFT processing on the range cell data from the pulse compression unit 30 in units of 1 CPI. FIG. 3 is a diagram schematically illustrating coherent integration by the Doppler filter processing unit 40.

Signal processor 50, the intensity of the range cell data from the Doppler filter processing unit 40, the range r, orientation theta, to be identified by the elevation angle φ and the relative speed v _m. That is, the signal processor 50, once all of the intensity of the range cell data range obtained by the scan r in all directions in a given search area, orientation theta, as specified by the elevation angle φ and the relative velocity v _m 4D data converted into is created. The four-dimensional data acquired by a certain scan i is represented as D ⁽ⁱ⁾ (r, θ, φ, v _m ). The signal processing unit 50 outputs the four-dimensional data to the integrating unit 60. FIG. 4 is a schematic diagram showing the relationship between the range r, the azimuth θ, the elevation angle φ, and the relative velocity v _m with respect to the target.

The target relative velocity v _m (n) in the nth (n is a natural number from 1 to M) frequency bin obtained based on M pulse signals transmitted at 1 CPI is obtained as follows. . The frequency bandwidth Δf of each frequency bin shown in FIG. 3 is Δf = f _PRF / M. Here, it is assumed that the frequency bin value occurs only due to the Doppler frequency due to target movement. Note that f _PRF = 1 / f _PRI . At this time, the relative velocity v _m (n) in the nth frequency bin is represented by v _m (n) = n · Δf · c / fc. However, c represents the speed of light and fc represents the carrier frequency.

  The prediction unit 70 receives integral four-dimensional data, which will be described later, from the integration unit 60, and assumes that a target exists in all the range bins specified by the integral four-dimensional data. Then, the prediction unit 70 predicts a range bin in which a target will exist at the next scan based on the relative speed of the integrated four-dimensional data. Processing in the prediction unit 70 at this time will be described below.

The radar apparatus receives reflected waves of transmission pulses that are sequentially irradiated in all directions in a predetermined search area. For this reason, receiving pulse signals from the same direction is discrete (one scan interval). If the period per scan is _TSCAN seconds, the frequency bank signal shown in FIG. 3 is obtained every period _TSCAN .

Assuming that the target motion model is a constant velocity linear motion, it can be predicted that the target has moved by R _m = v _m · T _SCAN at the next scan after T _SCAN seconds. Based on the moving amount _{R m,} moving range bin _{R mm} of the target _is calculated by _{R mm = round (R m)} . Here, the spaced adjacent range bins and _{x, R mm is} obtained and _{(v m · T SCAN / x} ) the largest integer less than or equal to.

When the integrated four-dimensional data is supplied from the integrating unit 60, the predicting unit 70 predicts a moving range bin group to which the target will move before the next scan based on the relative speed of the integrated four-dimensional data. . Here, the moving range bin group is represented as R = [R _mm , R _mm +1, R _mm −1]. When the range bin of the received integrated four-dimensional data is r, the prediction unit 70 predicts that a target exists in the range bins r + R _mm , r + R _mm +1, r + R _mm −1. The prediction unit 70 creates predicted four-dimensional data predicted to have a target in the range bins r + R _mm , r + R _mm +1, r + R _mm −1, and outputs the created predicted four-dimensional data to the recording unit 80.

  The recording unit 80 records the predicted four-dimensional data from the prediction unit 70. When the signal processing unit 50 creates new four-dimensional data for scanning, the recording unit 80 outputs the recorded predicted four-dimensional data to the integrating unit 60. Note that the recording unit 80 does not output the predicted four-dimensional data to the integrating unit 60 when the predicted four-dimensional data is not recorded.

  The integration unit 60 includes an addition unit 61 and an extraction unit 62.

  When the predicted four-dimensional data is supplied from the recording unit 80 to the integrating unit 60, the adding unit 61 receives the four-dimensional data from the signal processing unit 50 and the predicted four-dimensional data from the recording unit 80. The adding unit 61 adds the four-dimensional data and the predicted four-dimensional data, and outputs the added data to the extracting unit 62.

Extraction unit 62 receives the data added together with 4-dimensional data and the predicted four-dimensional data from the adder 61, the range bin _r + _{R mm,} of _{r + R mm + 1, r} + R mm -1, and extracts a large range bins of the most strength. The extraction unit 62 outputs the data about the extracted range bin to the prediction unit 70 and the subsequent stage as integrated four-dimensional data.

  When the predicted four-dimensional data is not supplied from the recording unit 80 to the integrating unit 60, the adding unit 61 outputs the four-dimensional data from the signal processing unit 50 to the extracting unit 62. The extraction unit 62 outputs the four-dimensional data from the addition unit 61 as integrated four-dimensional data to the prediction unit 70 and the subsequent stage.

  Although not shown in FIG. 1, the radar apparatus may further include a target detection unit at the subsequent stage of the integration unit 60. The target detection unit determines whether or not the intensity of the integrated four-dimensional data from the integration unit 60 exceeds a threshold value. The threshold value varies based on the number of incoherent integrations in the integration unit 60. The target detection unit determines that the target has been detected when the intensity of the integrated four-dimensional data exceeds the threshold value.

  Next, the operation when the integrating unit 60 and the predicting unit 70 of the radar apparatus configured as described above create integrated four-dimensional data will be described in detail. FIG. 5 is a sequence diagram when the integration unit 60 and the prediction unit 70 according to the first embodiment create integrated four-dimensional data. FIG. 6 is a diagram schematically showing integrated four-dimensional data created by the integration process shown in FIG.

First, the adding unit 61 receives the four-dimensional data D ₁ ⁽ⁱ⁾ (r, θ, φ, v _m ) obtained from the i-th scan from the signal processing unit 50 (sequence S51), and receives the received four-dimensional data. Is output to the extraction unit 62 (sequence S52).

The extraction unit 62 outputs the four-dimensional data from the addition unit 61 as integrated four-dimensional data D ₁ ⁽ⁱ⁾ (r, θ, φ, v _m ) to the prediction unit 70 and the subsequent stage (sequence S53).

The predicting unit 70 receives the integrated four-dimensional data from the extracting unit 62, and based on the relative velocity v _m of the integrated four-dimensional data, sets the moving range bin group R = [R _mm , R _mm +1, R _mm −1]. Predict. Based on the moving range bin group R, the prediction unit 70 predicts four-dimensional data D ₁ ^{(i + 1)} (r + R _mm , θ, φ, v _m ), D ₁ ^{(i + 1)} (r + R _mm +1, θ, φ, v _m). ), D ₁ ^{(i + 1)} (r + R _mm −1, θ, φ, v _m ) is created (sequence S54). The prediction unit 70 outputs the generated predicted four-dimensional data to the recording unit 80 (sequence S55). The recording unit 80 records the predicted four-dimensional data from the prediction unit 70 (sequence S56).

Next, the adding unit 61 obtains the four-dimensional data D ₂ ^{(i + 1)} (r + R _mm , θ, φ, v _m ), D ₂ ^{(i + 1)} (r + R _mm +1 ⁾ obtained from the signal processing unit 50 in the i + 1 th scan. , Θ, φ, v _m ), D ₂ ^{(i + 1)} (r + R _mm −1, θ, φ, v _m ), and predicted four-dimensional data D ₁ ^{(i + 1)} (r + R _mm , θ ⁾ recorded in the recording unit 80. , Φ, v _m ), D ₁ ^{(i + 1)} (r + R _mm +1, θ, φ, v _m ), D ₁ ^{(i + 1)} (r + R _mm −1, θ, φ, v _m ) are received (sequence S57). These are added together (sequence S58). In FIG. 6, because the target actually moves by R _mm ,

Among them, D _2,1 ^{(i + 1)} (r + R _mm , θ, φ, v _m ) takes the maximum value. The extraction unit 62 extracts D _2,1 ^{(i + 1)} (r + R _mm , θ, φ, v _m ) that takes the maximum value from the sum of the four-dimensional data and the predicted four-dimensional data (sequence) S510), and outputs the integrated four-dimensional data to the prediction unit 70 and the subsequent stage (sequence S511).

The prediction unit 70 receives the integrated four-dimensional data D _2,1 ^{(i + 1)} (r + R _mm , θ, φ, v _m ) from the extraction unit 62, and based on the integrated four-dimensional data, predicts four-dimensional data D _{2. , 1} ^{(i + 2)} (r + 2R _mm , θ, φ, v _m ), D _2,1 ^{(i + 2)} (r + 2R _mm +1, θ, φ, v _m ), D _2,1 ^{(i + 2)} (r + 2R _mm −1, θ, φ, v _m ) is created (sequence S512). The prediction unit 70 outputs the generated predicted four-dimensional data to the recording unit 80 (sequence S13). The recording unit 80 records the predicted four-dimensional data from the prediction unit 70 (sequence S514).

  Thereafter, the integration unit 60 and the prediction unit 70 create the integrated four-dimensional data by repeating the sequences S57 to S514, and output the generated integrated four-dimensional data to the subsequent stage.

Further, a case will be described in which the target that has moved by R _mm between scans up to i + 2 in FIG. 6 has moved by R _mm +1 in the i + 3rd scan. The adder 61 obtains four-dimensional data D ₄ ^{(i + 3)} (r + 3R _mm , θ, φ, v _m ), D ₄ ^{(i + 3)} (r + 3R _mm +1, θ, φ, v _m ) obtained in the i + 3rd scan. , D ₄ ^{(i + 3)} (r + 3R _mm −1, θ, φ, v _m ) and predicted four-dimensional data D ₃ ^{(i + 3)} (r + 3R _mm , θ, φ, v _m ), D recorded in the recording unit 80. ₃ ^{(i + 3)} (r + 3R _mm +1, θ, φ, v _m ) and D ₃ ^{(i + 3)} (r + 3R _mm −1, θ, φ, v _m ) are added together. Here, since the target actually moves by R _mm +1,

Of these, D _4,2 ^{(i + 3)} (r + 3R _mm +1, θ, φ, v _m ) takes the maximum value. The extraction unit 62 extracts D _4,2 ^{(i + 3)} (r + 3R _mm +1, θ, φ, v _m ) that takes the maximum value from the sum of the four-dimensional data and the predicted four-dimensional data, The integrated four-dimensional data is output to the prediction unit 70 and the subsequent stage.

Next, a simulation result of detection probability transition by the radar apparatus having the above configuration will be shown. FIG. 7 shows simulation specifications for the radar apparatus according to the first embodiment. 7A shows the transmission specifications, FIG. 7B shows the reception specifications, and FIG. 7C shows the target specifications. FIG. 8 is a diagram illustrating a simulation result of detection probability transition using the simulation specifications of FIG. FIG. 8A shows a simulation result of a conventional radar apparatus that performs signal synthesis based on a moving range bin predicted by adding R _mm to a received range bin. FIG. 8B shows a simulation result of this embodiment in which signal synthesis is performed based on a moving range bin predicted by adding R _mm , R _mm +1, and R _mm −1 to the received range bin. . In this simulation, the distance between the target and the receiver in the first scan is changed to all 11 patterns indicating the distance between the target and the receiver in the target specifications, and the signals received up to 10 scans in each distance pattern are combined. The detection probability evaluation is performed. It is assumed that the number of range cells to be moved is different from the other scans in the fourth and ninth scans.

  8A and 8B, it is difficult to understand the performance difference between the radar apparatus according to this embodiment and the conventional radar apparatus. Therefore, in FIG. 8A and FIG. 8B, the target / transmitter-receiver distance satisfying the detection probability 0.5 is compared. FIG. 9 shows a simulation result indicating the maximum detection distance between the radar apparatus according to the present embodiment and the conventional radar apparatus. The maximum detection distance indicates a target / transmitter-receiver distance that satisfies the detection probability 0.5.

  According to FIG. 9, in the conventional radar apparatus, the maximum detection distance decreases in 4 scans and 9 scans. That is, if the number of range cells to be moved is different from other scans, the detection probability is reduced. On the other hand, in the radar apparatus according to the present embodiment, the maximum detection distance increases for each scan. That is, even if the number of range cells to move is different from other scans, the detection probability increases for each scan.

  As described above, in the first embodiment, the prediction unit 70 predicts a moving range bin group between scans, and creates predicted four-dimensional data based on the predicted moving range bin group. The adding unit 61 adds the four-dimensional data actually acquired in the next scan to the generated predicted four-dimensional data. Then, the extraction unit 62 extracts, as integrated four-dimensional data, data about the range bin that indicates the highest intensity among the data obtained by adding the predicted four-dimensional data and the four-dimensional data. Output.

  Assuming that the target motion model is a constant velocity linear motion, the moving range bin predicted by the prediction unit 70 based on the relative velocity is usually a constant amount and an integer value. On the other hand, an actual target does not always move with a constant moving range bin for each scan due to some unsteady factor on the radar apparatus side or the target side, even when a constant linear motion is performed. The target movement amount includes a fraction. Due to these causes, the moving range bin between scans is likely to cause a fluctuation of about ± 1 range over a plurality of scans. Therefore, there is a high possibility of an error between the movement range bin predicted on the radar side and the actual movement amount of the target.

On the other hand, in the radar apparatus according to the present embodiment, prediction is made up to a range of ± 1 of the moving range bin R _mm calculated from the relative speed. Thus, even if an error occurs between the predicted movement range bin and the actual movement amount, R _mm +1 or R _mm −1 and the actual movement amount coincide with each other, so that the four-dimensional data and the prediction are performed. Integration with 4D data will be achieved.

  Therefore, according to the radar apparatus according to the first embodiment, the data estimated based on the past scan result can be accurately integrated into the data obtained in the current scan.

(Second Embodiment)
FIG. 10 is a block diagram showing a configuration of a MIMO radar system including the radar apparatus according to the second embodiment. Each radar apparatus receives a pulse signal in which transmission pulses transmitted from the transmission apparatuses TX1 to TXR are reflected by a target. Note that the transmission pulses transmitted from the transmission devices TX1 to TXR are modulated so as to be uncorrelated with each other. Further, the origin of coordinates and the orthogonal axis are shared in a plurality of radar apparatuses.

  FIG. 11 is a block diagram illustrating a functional configuration of a radar apparatus according to the second embodiment. The radar apparatus shown in FIG. 11 includes a radio unit 10, a spatial processing unit 20, a pulse compression unit 30, a Doppler filter processing unit 40, a signal processing unit 90, an integration unit 100, a prediction unit 110, and a recording unit 80.

The signal processing unit 90 records in advance the origin and orthogonal axes of coordinates shared among the radar devices. In addition, the signal processing unit 90 grasps the position coordinates of the own device. In the signal processing unit 90, the intensity of the range cell data from the Doppler filter processing unit 40 is specified by the x coordinate, y coordinate, z coordinate of the target position, and the x coordinate, y coordinate, z coordinate of the target speed. So that That is, the signal processing unit 90 determines the 6-dimensional cell data F in which the strength of the range cell data is specified by the x-coordinate, y-coordinate, z-coordinate of the target position, and the x-coordinate, y-coordinate, and z-coordinate of the target velocity. (X, y, z, v _x , v _y , v _z ) is created. The signal processing unit 90 outputs the 6-dimensional cell data to the integration unit 100.

When the integration unit 100 is supplied with integral 6-dimensional cell data (to be described later) from the integration unit 100, the prediction unit 110 is based on the speed of the integral 6-dimensional cell data, and the moving range bin group to which the target will move before the next scan. Predict. Assuming that the target motion model is constant-velocity linear motion, the target specified by the 6-dimensional cell data F (x, y, z, v _x , v _y , v _z ) is determined during the next scan after T _SCAN seconds. F can be predicted _{(x + R mx, y +} R my, z + R mz, v x, v y, v z) and is identified by. _{Wherein, R mx = x + v x} T SCAN, R my = y + v y T SCAN, an _{R mz = z + v z T} SCAN. The amount of movement _{(R mx, R my, R} mz) based on the target of the movement range bin _{(R mmx, R mmy, R} mmz) _{is, R mmx = round (R mx} ), R mmy = round (R my), R _mmz = round (R _mz ). When placing the spacing between adjacent range bins and d, the target of the movement range bin _{(R mmx, R mmy, R} mmz) _{are, (v x · T SCAN /} d, v y · T SCAN / d, v z · T SCAN / d) It is obtained by the following maximum integer.

The prediction unit 110 predicts the moving range bin group based on the integrated 6-dimensional cell data supplied from the integration unit 100. The moving range bin group, moving range bin _{(R mmx, R mmy, R} mmz) , and includes moving range bin _{(R mmx, R mmy, R} mmz) at least one of the moving range bin of the range of ± 1 around the can . The prediction unit 110 creates predicted 6-dimensional cell data based on the moving range bin group, and outputs the created predicted 6-dimensional cell data to the storage unit 120.

  The recording unit 120 records the predicted 6-dimensional cell data from the prediction unit 110. The recording unit 120 outputs the recorded predicted 6-dimensional cell data to the integrating unit 100 when the signal processing unit 90 creates 6-dimensional cell data for a new scan. Note that the recording unit 120 does not output the predicted 6-dimensional cell data to the integrating unit 100 when the predicted 6-dimensional cell data is not recorded.

  The integration unit 100 includes an addition unit 101, an extraction unit 102, and a MISO (Multi Input Single Output) integration unit 103.

  The MISO integration unit 103 performs MISO integration on the 6-dimensional cell data from the signal processing unit 90. MISO integration is a process of integrating 6-dimensional cell data for a pulse signal based on a plurality of transmission pulses. At this time, the pulse signal is obtained by reflecting, scattering, or diffracting the transmission pulse with the same target. Hereinafter, MISO integration of 6-dimensional cell data will be described.

  The transmission apparatuses TX1 to TXR direct the transmission beam toward the target at different times. Therefore, the pulse signals for the transmission pulses from the transmission devices TX1 to TXR are received by the radar device at different times. In addition, since the transmission devices TX1 to TXR have different times for directing the transmission beam toward the target, the target may move during that time. Therefore, the 6-dimensional cell data obtained based on the pulse signal from the same target is different for each transmission source.

The MISO integration unit 103 defines a target motion model in order to predict the amount of movement of the target that has moved while directing the transmission beam. For example, assuming that the target motion model is constant velocity linear motion, the 6-dimensional cell data F (x, y, z, v _x , v _y , v _z ) at a certain time is F ( x + v _x Δt, y + v _y Δt, z + v _z Δt, v _x , v _y , v _z ).

  The MISO integration unit 103 connects the 6-dimensional cell data before movement and the 6-dimensional cell data after movement based on the assumed motion model. Then, the MISO integration unit 103 integrates the combined 6-dimensional cell data. Thus, by predicting the 6-dimensional cell data after movement based on the motion model, the reception times of the pulse signals from which the transmission pulses from the transmission devices TX1 to TXR are reflected to the same target are different. It is possible to integrate 6-dimensional cell data based on the pulse signal.

  When the predicted 6-dimensional cell data is supplied from the recording unit 120 to the integrating unit 100, the adding unit 101 receives the 6-dimensional cell data after the MISO integration and the predicted 6-dimensional cell data from the recording unit 120. The addition unit 101 adds the 6-dimensional cell data and the predicted 6-dimensional cell data, and outputs the added data to the extraction unit 102.

Extraction unit 102 receives the 6-dimensional cell data and the predicted six-dimensional cell data and is summed data from the adder 101, the range bin _{(r + R mmx, r +} R mmy, r + R mmz), and, the range bin _{(r + R mmx, r +} R mmy, Among the range bins in the range of ± 1 around r + R _mmz ), the range bin having the highest intensity is extracted. The extraction unit 102 outputs the data about the extracted range bin to the prediction unit 110 and the subsequent stage as integrated 6-dimensional cell data.

  When the predicted 6-dimensional cell data is not supplied from the recording unit 120 to the integrating unit 100, the adding unit 101 outputs the 6-dimensional cell data after the MISO integration to the extracting unit 102. The extraction unit 102 outputs the 6-dimensional cell data from the addition unit 101 to the prediction unit 110 and the subsequent stage as integrated 6-dimensional cell data.

  The integrated 6-dimensional cell data from the integration unit 100 is output to the processing server 130. The processing server 130 performs single input multi output (SIMO) integration on the integrated 6-dimensional cell data respectively acquired by a plurality of connected radar devices. Then, the processing server 130 determines that the target has been detected when the level of the result of the SIMO integration exceeds the threshold value set according to the integration number of the integrated 6-dimensional cell data.

As described above, in the second embodiment, the prediction unit 110 predicts a moving range bin group between scans, and creates predicted 6-dimensional cell data based on the predicted moving range bin group. The adding unit 101 adds the 6-dimensional cell data actually obtained in the next scan to the created predicted 6-dimensional cell data. Then, the extraction unit 102 extracts the data having the highest intensity from the sum of the predicted 6-dimensional cell data and the 6-dimensional cell data as integrated 6-dimensional cell data, and outputs the integrated 6-dimensional cell data to the subsequent stage and the prediction unit 110. I have to. Thus, even when the error occurs between the actual amount of movement predicted movement range _{bin, (R mmx, R mmy,} R mmz) with any of the moving range bin to be included within the scope of ± 1 relative to the Since the actual amount of movement coincides, the integration of the 6-dimensional cell data and the predicted 6-dimensional cell data is achieved.

  Therefore, according to the radar apparatus according to the second embodiment, the data estimated based on the past scan result can be accurately integrated into the data obtained in the current scan.

  In the second embodiment, the case where the moving range cell group is calculated only by the prediction unit 110 has been described as an example. However, the present invention is not limited to this. For example, the MISO integration unit 103 may calculate the moving range cell group.

The MISO integration unit 103 defines a target motion model in order to predict the amount of movement of the target that has moved while directing the transmission beam. For example, assuming that the target motion model is constant velocity linear motion, the 6-dimensional cell data F (x, y, z, v _x , v _y , v _z ) at a certain time is F ( x + v _x Δt, y + v _y Δt, z + v _z Δt, v _x , v _y , v _z ).

Based on the assumed motion model, the MISO integration unit 103 predicts up to ± 1 range of the moving range bins R _mm , R _mm +1, and R _mm −1 calculated from the relative speed, and is the largest among the predicted 6-dimensional data. The 6-dimensional cell data after the movement is taken as the one having the value of 6 and the 6-dimensional cell data before the movement and the 6-dimensional cell data after the movement are linked. Then, the MISO integration unit 103 integrates the combined 6-dimensional cell data.

In the above embodiments were described moving range bin _{R mm, R mmx, R mmy} , the case of forming a moving range bins groups with a width of each of ± 1 to _{R MMZ} example. However, the present invention is not limited to this. For example, the moving range bin group may be formed with a width of ± 2.

  In each of the above embodiments, predicted 4D data or predicted 6D cell data in the next scan is created based on the integrated 4D data or the integrated 6D cell data, and these are recorded in the recording units 80 and 120. The case has been described as an example. However, the present invention is not limited to this. For example, integrated 4D data or integrated 6D cell data is recorded in the recording unit, and when new 4D data or 6D cell data is created, the integrated 4D data or integrated 6D cell read from the recording unit. Predicted four-dimensional data or predicted six-dimensional cell data may be created based on the data.

  Although several embodiments have been described, these embodiments have been presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and the equivalents thereof.

  DESCRIPTION OF SYMBOLS 10 ... Radio | wireless part, 11 ... Antenna element, 12 ... Reception module, 13 ... Frequency conversion part, 14 ... A / D, 20 ... Spatial processing part, 30 ... Pulse compression part, 40 ... Doppler filter processing part, 50, 90 ... Signal processing unit, 60, 100 ... integration unit, 61, 101 ... addition unit, 62, 102 ... extraction unit, 70, 110 ... prediction unit, 80, 120 ... recording unit, 103 ... MISO integration unit, 130 ... processing server

Claims (6)

A radio unit for receiving a pulse signal;
A pulse compression unit that performs pulse compression processing on the pulse signal and generates range cell data for each pulse signal;
Doppler filter processing unit that generates range cell data for each frequency bin by performing Doppler filter processing on the range cell data from the pulse compression unit;
A signal processing unit that converts range cell data acquired for each scan by the Doppler filter processing unit into specific data that is specified by parameters including a target position and velocity;
A prediction unit that creates prediction data in which the target is predicted to be located within a preset range from the position predicted based on the position and speed of the target obtained from the previous scan result;
An addition unit that adds the prediction data and the unique data acquired at the time of the next scan at the same position;
The data of the position where intensity | strength is the maximum is extracted among the data added together in the said same position, The extraction part which comprises the extracted data as a scanning result to the said prediction part and a back | latter stage is provided, It is characterized by the above-mentioned. Radar device.   When the target is located in a range bin obtained by adding a movement amount between scans based on the speed indicated by the scan result to the range bin indicated by the scan result, and a range bin in a range set in advance from the range bin The radar apparatus according to claim 1, wherein prediction is performed.   The signal processing unit converts the range cell data acquired for each scan into specific data specified by a range, an azimuth and elevation angle based on a beam position, and a relative velocity based on a frequency bin. The radar apparatus according to claim 1 or 2. The pulse signal is obtained by reflecting, scattering, or diffracting a plurality of transmission pulses modulated so as to be uncorrelated with each other.
The signal processing unit converts the range cell data acquired for each scan into specific data specified by a Cartesian coordinate system and speed using a preset origin and orthogonal axes,
5. A MISO integration unit that integrates unique data derived from different transmission pulses in consideration of a change based on a difference in reception time of the plurality of pulse signals, and outputs the integrated data to the addition unit. Item 3. The radar device according to item 1 or 2.   5. The radar according to claim 4, wherein the MISO integration unit integrates unique data derived from the different transmission pulses in consideration of a preset range with respect to a change based on the difference in reception time. apparatus. Receive the pulse signal,
Apply pulse compression processing to the pulse signal to generate range cell data for each pulse signal,
By performing Doppler filter processing on the range cell data after pulse compression, range cell data for each frequency bin is generated,
The range cell data after the Doppler filter processing acquired for each scan is converted into specific data specified by parameters including a target position and velocity,
The unique data and the prediction data for predicting that the target is positioned within a preset range from the position predicted based on the target position and speed obtained from the previous scan result are added together at the same position,
Of the data added together at the same position, extract the data of the position where the intensity is maximum and output to the subsequent stage,
A received data processing method, wherein prediction data for predicting a plurality of target positions at the time of the next scan is created based on the extracted data.

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