JP7173785B2 - Target detection device and target detection method - Google Patents

Description

The present invention relates to a target object detection device and a target object detection method.

Conventionally, as a target detection device for detecting a target, there has been proposed a radar device that transmits a frequency-modulated signal and detects target information including the distance and relative speed to the target (see, for example, Patent Document 1).

JP 2016-3873 A

However, the above-described radar device has room for improvement in terms of early determination of the target type based on detected target information. Specifically, conventionally, when trying to determine the type of a target, the type is determined by combining a plurality of target information acquired in one scan, or target information derived from one target is determined. Since the type is determined based on the change over time, the time required for determination processing increases.

SUMMARY OF THE INVENTION It is an object of the present invention to provide a target detection apparatus and a target detection method capable of early determination of the type of a target.

In order to solve the above-described problems and achieve the object, a target object detection device according to the present invention includes a generation section and a determination section. The generator performs frequency analysis on a beat signal obtained by mixing a frequency-modulated transmission wave and a reflected wave of the transmission wave from a target, thereby generating two-dimensional data in the direction of distance and the direction of relative velocity. Generate a frequency spectrum. The determination unit determines the type of the target based on the spread in the distance direction of a distribution shape around a peak in the two-dimensional frequency spectrum generated by the generation unit.

According to the present invention, the type of target can be determined early.

FIG. 1A is a diagram showing an overview of a target detection method according to an embodiment. FIG. 1B is a diagram illustrating an outline of a target detection method according to the embodiment; FIG. 2 is a block diagram of the radar device. FIG. 3 is a diagram showing the processing contents of the generation unit. FIG. 4 is a diagram showing the processing contents of the generation unit. FIG. 5 is an explanatory diagram of model information. FIG. 6 is a diagram showing determination processing of the determination unit. FIG. 7 is a diagram showing determination processing of the determination unit. FIG. 8 is a flow chart showing the procedure of determination processing executed by the radar device.

Hereinafter, embodiments of a target object detection device and a target object detection method disclosed in the present application will be described in detail with reference to the accompanying drawings. It should be noted that the present invention is not limited by this embodiment. Moreover, below, the case where the radar apparatus which is a target object detection apparatus which concerns on embodiment performs a target object detection method is demonstrated.

First, the outline of the target object detection method according to the embodiment will be described with reference to FIGS. 1A and 1B. 1A and 1B are diagrams showing an outline of a target detection method according to an embodiment. FIG. 1A shows an own vehicle MC equipped with a radar device 1 and another vehicle OC which is a truck preceding the own vehicle MC in a lane adjacent to the own vehicle MC.

As shown in FIG. 1A, the radar device 1 according to the embodiment is mounted, for example, on the front end of the own vehicle MC, and detects moving objects such as other vehicles OC and targets such as stationary objects. Further, the radar device 1 shown in FIG. 1A is, for example, a radar device of the FCM (Fast Chirp Modulation) method.

The FCM method is a method that detects target information including the distance and relative speed to each target within the detection range by outputting a transmission wave in which multiple chirp waves with continuously changing frequencies are repeated. be.

Specifically, the FCM radar apparatus 1 generates target information by performing "frequency analysis processing", "peak extraction processing", and "target detection processing".

In the "frequency analysis process", frequency analysis is performed on a beat signal obtained by mixing a frequency-modulated transmission wave (chirp wave) and a reflected wave of the transmission wave from the target. Specifically, in the "frequency analysis processing", two-dimensional fast Fourier transform processing (hereafter, two-dimensional FFT processing) generates a two-dimensional frequency spectrum in the distance direction and the relative velocity direction. In the two-dimensional frequency spectrum, each frequency corresponding to the distance (longitudinal distance) to the target (hereinafter referred to as distance bin) and each frequency corresponding to the relative speed with the target (hereinafter referred to as velocity bin) peak is included (see FIG. 1B).

In the "peak extraction process", a peak candidate whose power (magnitude of peak candidate) in the generated two-dimensional frequency spectrum is equal to or greater than a predetermined value is extracted as a peak. In the "target detection process", the distance and relative speed of the target are detected based on the extracted peaks. Specifically, in the "target detection process", the distance bin corresponding to the peak is detected as the distance of the target, and the speed bin is detected as the relative speed of the target.

In the target object detection method according to the embodiment, the two-dimensional frequency spectrum obtained by the "frequency analysis process" is used to roughly determine the target type before the "peak extraction process". The type of target is a category classified according to the difference in the length of the target in the distance direction, such as truck, passenger car, and person.

Here, target type determination by a conventional target detection method will be described. In conventional target detection methods, when trying to determine the type of a target, determination is made by combining a plurality of target information obtained in one scan, or target information derived from one target is determined. Since determination is made based on time change (that is, target information of multiple scans), the time required for determination processing increases.

For example, when determining the type of a target by combining a plurality of pieces of target information, a plurality of pieces of target information are required for one target, and the target type will be judged. That is, in order to determine the type of target, at least "target detection processing" needs to be performed, which increases the processing time.

Further, for example, when the type of target is determined based on changes in target information over time, it is necessary to obtain target information for a plurality of scans, which increases the processing time. Thus, conventionally, there is room for improvement in early determination of the target type.

Therefore, in the target detection method according to the embodiment, the target type is roughly determined in one scan and before the "peak extraction process". Specifically, in the target detection method according to the embodiment, based on the spread in the distance direction of the distribution shape (hereinafter referred to as peak distribution) around the peak candidate in the two-dimensional frequency spectrum generated by the "frequency analysis process" to determine the type of target.

FIG. 1B shows a two-dimensional frequency spectrum generated by the “frequency analysis process” and a distribution model of peak distribution in the two-dimensional frequency spectrum (truck and passenger car in FIG. 1B). The distribution model shown in FIG. 1B is a map image in which the power around the peak candidate is arranged as the intensity of each pixel on a two-dimensional plane with distance bins and velocity bins as coordinate axes. The stronger the power, the darker the pixel intensity. It's becoming Such a distribution model is generated in advance by, for example, an experiment or the like, and this point will be described later.

As shown in FIG. 1B, it can be seen that the distribution model for trucks has a wider range of distance bins than the distribution model for passenger cars. In other words, in the case of trucks, the spread of the peak distribution in the distance direction is greater than in the case of passenger cars.

Then, the radar device 1 according to the embodiment searches for a peak distribution similar to the distribution model in the obtained two-dimensional frequency spectrum. When a peak distribution similar to the distribution model of a truck (or a passenger car) exists in the two-dimensional frequency spectrum, the radar device 1 detects that the type of target is a truck (or a passenger car). ).

That is, in the target detection method according to the embodiment, the target type is determined using the correlation between the spread of the peak distribution in the distance direction and the length of the target in the distance direction. Therefore, in the radar device 1 according to the embodiment, it is possible to determine the type of the target in one scan and before the "peak extraction process". can.

In the radar device 1 according to the embodiment, in addition to the type of target, it is determined whether the target is leaving or approaching the own vehicle MC, and whether the target is before or after overtaking the own vehicle MC from an adjacent lane. can be determined, which will be described later.

Next, the configuration of the radar device 1 according to the embodiment will be described using FIG. FIG. 2 is a block diagram of the radar device 1. As shown in FIG. As shown in FIG. 2 , the radar device 1 is connected to a vehicle control device 2 .

The vehicle control device 2 performs vehicle control such as PCS (Pre-crash Safety System) and AEB (Advanced Emergency Braking System) based on the target detection result by the radar device 1 . Note that the radar device 1 may be used for various purposes other than the vehicle-mounted radar device (for example, monitoring of airplanes and ships, etc.).

The radar device 1 includes a transmitter 10 , a receiver 20 and a processor 30 . The transmitter 10 includes a signal generator 11 , an oscillator 12 and a transmission antenna 13 . The signal generator 11 generates a modulated signal whose voltage changes like a sawtooth wave, and supplies the modulated signal to the oscillator 12 . The oscillator 12 generates a chirp signal ST based on the modulated signal generated by the signal generator 11 and outputs the chirp signal ST to the transmission antenna 13 .

The transmission antenna 13 converts the chirp signal ST input from the oscillator 12 into a transmission wave SW, and outputs the transmission wave SW to the outside of the vehicle MC. A transmission wave SW output from the transmission antenna 13 has a waveform in which a plurality of chirp waves Ch1 to Chn are repeated. A transmission wave SW transmitted from the transmission antenna 13 to the front of the own vehicle MC is reflected by a target such as another vehicle OC to become a reflected wave.

The receiving section 20 includes a plurality of receiving antennas 21a-21d forming an array antenna, mixers 22a-22d and A/D converters 23a-23d. Each receiving antenna 21 receives a reflected wave from a target as a receiving wave RW, converts the receiving wave RW into a receiving signal SR, and outputs the receiving signal SR to a mixer 22 provided for each receiving antenna 21 . Although the number of receiving antennas 21 shown in FIG. 2 is four, it may be three or less or five or more.

A received signal SR output from each receiving antenna 21 is input to the mixer 22 after being amplified by an amplifier (for example, a low noise amplifier) not shown. The mixer 22 mixes a part of the chirp signal ST and the received signal SR to remove unnecessary signal components, generates a beat signal SB, and outputs the beat signal SB to the A/D converter 23 .

As a _result , _{the beat} frequency _{f SB} ( = f _ST −f _SR ) is generated. The beat signal SB generated by the mixer 22 is output to the processing section 30 after being converted into a digital signal by the A/D converter 23 .

The processing unit 30 includes a transmission control unit 31 , a signal processing unit 32 and a storage unit 33 . The signal processing section 32 includes a generation section 321 , a map generation section 322 , a determination section 323 , a peak extraction section 324 , a calculation section 325 and an output section 326 . The storage unit 33 stores model information 331 .

The processing unit 30 is, for example, a microcomputer including a CPU (Central Processing Unit), ROM (Read Only Memory), RAM (Random Access Memory), input/output ports, etc., and controls the radar device 1 as a whole.

The CPU of such a microcomputer functions as a transmission control section 31 and a signal processing section 32 by reading and executing programs stored in the ROM. At least a part or all of the transmission control unit 31 and the signal processing unit 32 can be configured by hardware such as ASIC (Application Specific Integrated Circuit) or FPGA (Field Programmable Gate Array).

The storage unit 33 corresponds to RAM. The model information 331 stored in the storage unit 33 is information indicating a distribution model of peak distribution in the two-dimensional frequency spectrum, and is generated in advance for each type of target.

The transmission control unit 31 controls the signal generation unit 11 of the transmission unit 10 and causes the signal generation unit 11 to output to the oscillator 12 a modulated signal whose voltage changes in a sawtooth pattern. As a result, a chirp signal ST whose frequency changes over time is output from the oscillator 12 to the transmitting antenna 13 .

The signal processing unit 32 performs two-dimensional FFT processing on the beat signals SB output from each A/D converter 23, and calculates the distance, relative velocity, and bearing of the target based on the result of the two-dimensional FFT processing. to calculate Processing of each unit of the signal processing unit 32 will be described below.

The generator 321 performs frequency analysis such as two-dimensional FFT on each beat signal SB output from each A/D converter 23 to generate a two-dimensional frequency spectrum in the direction of distance and the direction of relative velocity. Here, the processing contents of the generation unit 321 will be specifically described with reference to FIGS. 3 and 4. FIG.

3 and 4 are diagrams showing the processing contents of the generation unit 321. FIG. Note that in FIG. 3, two thick downward white arrows divide the area into three areas, and these areas are described as upper, middle, and lower in order from the top.

First, the point that the beat signal is generated by the transmission processing by the transmission section 10 and the reception processing by the reception section 20 has already been described. As a result, as shown in the upper part of FIG. 3, a beat signal having a beat frequency f _SB (=fST-fSR), which is the difference between the transmission frequency f _ST and the reception frequency f _SR , is generated for each chirp wave. Here, the beat signal obtained by the first chirp wave Ch1 is defined as "B1", the beat signal obtained by the second chirp wave Ch2 is defined as "B2", and the beat signal obtained by the nth chirp wave Chn. is "Bn".

In the example shown in the upper part of FIG. 3, the transmission frequency f _ST increases with time from the reference frequency f0 with a slope θ (=(f1−f0)/Tm) and reaches the maximum frequency f1. It is a sawtooth wave that returns to the reference frequency f0 in a short time after reaching it. Also, the modulation frequency Δf of the chirp wave can be expressed as Δf=f1−f0.

Although not shown, the transmission frequency f _ST reaches the maximum frequency f1 from the reference frequency f0 in a short time for each chirp wave, and the slope θ (=(f1−f0 )/Tm) and reach the reference frequency f0.

The generation unit 321 first performs “first FFT processing” on each beat signal generated and input in this way. As described above, the transmission wave based on the transmission signal is transmitted from the transmission antenna 13, and the transmission wave is reflected by the target to become a reflected wave. is output as The period from when the transmission wave is transmitted from the transmission antenna 13 to when the reception signal is output increases or decreases in proportion to the distance between the target and the radar device 1, and the beat frequency f _SB is the frequency of the beat signal. is proportional to the distance between the target and the radar device 1 .

Therefore, in the frequency spectrum of the beat signal generated by performing the first FFT processing on the beat signal, a peak appears in the frequency bin fr (distance bin fr) corresponding to the distance to the target. Therefore, by specifying the distance bin fr in which such a peak exists, the distance to the target can be detected.

By the way, when the relative velocity between the target and the radar device 1 is zero, no Doppler component occurs in the received signal, and the phases of the received signals corresponding to the chirp waves are the same. The phase is also the same. On the other hand, when the relative velocity between the target and the radar device 1 is not zero, a Doppler component is generated in the received signal, and the phases of the received signals corresponding to the chirp waves are different. A change in phase appears in response to the Doppler frequency.

The middle part of FIG. 3 shows an example of the peak phase change between the first FFT processing result of the beat signals (B1 to B8) that are temporally continuous and the beat signals. In such an example, there is a peak at the same range bin fr10, indicating that the phase of such peaks is changing.

In this way, when the relative velocity between the target and the radar device 1 is not zero, a phase change corresponding to the Doppler frequency appears in the peak of the same target between the beat signals. Therefore, by arranging the frequency spectrum obtained by the first FFT processing of each beat signal in time series and performing the “second FFT processing” as shown in the lower part of FIG. The emerging frequency spectrum can be obtained. That is, the generation unit 321 performs two FFT processes, which are frequency analysis, to generate a two-dimensional frequency spectrum in which peaks appear for each distance bin (distance direction) and velocity bin (relative velocity direction) shown in FIG. can be obtained. Note that the calculation unit 325 in the latter stage can detect the relative speed with respect to the target by detecting the frequency bin in which such a peak appears, that is, the speed bin.

Returning to FIG. 2, the map generator 322 will be described. The map generator 322 generates map information that maps the peak distribution based on the two-dimensional frequency spectrum generated by the generator 321 .

For example, the map generation unit 322 generates, as map information, a map image obtained by converting spectrum information arranged on a two-dimensional plane with distance bins and velocity bins as coordinate axes into image information. The image of the map can express, for example, the power by a color system such as RGB of pixels, the density of the color (for example, shading), and the like. Note that the map generation unit 322 is not limited to converting spectrum information into a map image. For example, the map generation unit 322 generates, as map information, a data matrix in which data values themselves are arranged on a two-dimensional plane with distance bins and speed bins as coordinate axes. You may

The determination unit 323 determines the target type based on the two-dimensional frequency spectrum generated by the generation unit 321 . Specifically, the determination unit 323 determines the target type based on the spread of the peak distribution in the distance direction (distance bin direction) in the two-dimensional frequency spectrum.

For example, the determination unit 323 determines the target type by comparing the distribution model of the model information 331 and the peak distribution in the two-dimensional frequency spectrum generated by the generation unit 321 . Here, the model information 331 will be specifically described with reference to FIG.

FIG. 5 is an explanatory diagram of the model information 331. As shown in FIG. FIG. 5 shows a distribution model in which the type of target is a truck and a distribution model in which the target is a passenger car.

As shown in FIG. 5, the distribution model in the model information 331 is map information obtained by mapping the peak distribution. Specifically, the model information 331 as map information is a map image obtained by discretely plotting peaks with distance bins and velocity bins as parameters on an image plane. In FIG. 5, the peak power is indicated by shading, and the darker the color, the higher the peak power.

As shown in FIG. 5, trucks have a wider range of range bins in the distribution model than cars. In other words, the spread in the distance direction in the distribution model is greater for trucks than for passenger cars.

That is, the model information 331 includes distribution models with different ranges of distance bins for each type of target, and the determination unit 323 determines that there is a peak distribution similar to each distribution model in the two-dimensional frequency spectrum. Determine whether or not it is included. By comparing the two-dimensional frequency spectrum and the distribution model in this manner, the target type can be determined with high accuracy.

Note that FIG. 5 describes a case where the distribution model of the model information 331 is expressed as a map image (for example, a grayscale image or a color image), but the distribution model is not limited to the map image. For example, a distribution model may represent each peak as a discrete data value.

Alternatively, the distribution model of the model information 331 may be a predetermined machine learning algorithm. Arbitrary algorithms such as neural networks, support vector machines, Bayesian networks, etc., can be used as the predetermined algorithms.

Specifically, the determination unit 323 can employ a template matching method when comparing the two-dimensional frequency spectrum and the distribution model. That is, the determination unit 323 scans the two-dimensional frequency spectrum map image using the distribution model map image, and detects a peak distribution whose similarity to the distribution model is equal to or greater than a predetermined threshold.

Any scale such as SAD (Sum of Absolute Difference), SSD (Sum of Squared Difference), or NCC (Normalized Cross-Correlation) can be used as the degree of similarity.

Note that the target type determination by the determination unit 323 is not limited to the template matching method. For example, the determination unit 323 may determine the target type by comparing the range of distance bins of the peak distribution in the two-dimensional frequency spectrum and the range of distance bins of the distribution model.

Specifically, when the difference between the distance bin range of the peak distribution in the two-dimensional frequency spectrum and the distance bin range of the distribution model is less than a predetermined value, the determination unit 323 determines the type of the distribution model. Determined as the target type of the peak distribution.

Further, when the distribution model of the model information 331 is a machine learning algorithm, the determination unit 323 may determine the target type by giving a two-dimensional frequency spectrum as input data to the algorithm. .

Further, the determination unit 323 can determine whether the target is approaching or leaving the host vehicle MC based on the two-dimensional frequency spectrum. This point will be described with reference to FIGS. 6 and 7. FIG.

6 and 7 are diagrams showing determination processing of the determination unit 323. FIG. FIG. 6 shows a situation in which a target, which is another vehicle OC in an adjacent lane, overtakes own vehicle MC. In such a case, the determination unit 323 can determine whether the target is approaching or leaving the own vehicle MC, and whether the target is before overtaking or after overtaking.

First, with reference to FIG. 6, the process of determining whether the target is approaching or leaving the host vehicle MC will be described. As shown in FIG. 6, when the target approaches the own vehicle MC, the peak distribution has a speed bin range on the negative side. In other words, when the target approaches the own vehicle MC, the peak distribution spreads in the relative velocity direction on the negative side.

Therefore, the determination unit 323 determines approach or separation from the characteristic of the peak distribution that spreads in the relative velocity direction. That is, the determination unit 323 determines that the target is approaching the own vehicle MC when the peak distribution spreads in the relative velocity direction on the negative side. On the other hand, when the peak distribution spreads in the relative velocity direction on the positive side, the determination unit 323 determines that the target has left the host vehicle MC.

In this manner, the determination unit 323 can determine whether the target is approaching or leaving the host vehicle MC prior to the subsequent relative velocity calculation by using the feature of the peak distribution spreading in the speed direction. That is, since a target or the like approaching the own vehicle MC can be detected early, the response of the vehicle control device 2 can be accelerated, for example.

Next, the process of determining whether the target is before or after overtaking the own vehicle MC will be described. As shown in FIG. 6, before the target overtakes the host vehicle MC, the peak distribution is characterized by being distorted in the speed direction. FIG. 7 schematically shows the distorted features before and after overtaking.

As shown in FIG. 7, the determination unit 323 determines whether the target is before or after overtaking the own vehicle MC by using the characteristics of distortion in the speed direction. In FIG. 7, lines connecting the bins with the largest power for each distance bin of the peak distribution before and after overtaking are shown before and after overtaking.

As shown in FIG. 7, the lines representing before and after overtaking are curves that are skewed in the direction of the speed bins. That is, when the peak distribution spreads in the negative speed direction and is distorted in the negative speed direction, the determination unit 323 determines that the target is before overtaking the host vehicle MC. I judge.

On the other hand, if the peak distribution spreads in the positive speed direction and is distorted in the positive speed direction, the determining unit 323 determines that the target has overtaken the host vehicle MC. I judge.

In this manner, the determination unit 323 can determine whether the vehicle is overtaking or after overtaking based on the distortion of the peak distribution in the speed direction. can respond.

Returning to FIG. 2, the peak extractor 324 will be described. The peak extraction unit 324 extracts peak candidates whose power is equal to or greater than a threshold from the peak candidates present in the two-dimensional frequency spectrum generated by the generation unit 321 as peaks. For example, the peak extraction unit 324 may consider the determination result of the determination unit 323 when the number of extracted peaks exceeds a specified number.

For example, the peak extraction unit 324 may preferentially extract a peak candidate to which type information is added, a peak candidate determined to be approaching, or a peak candidate determined to be before overtaking, based on the determination result of the determination unit 323. good. Thereby, the safety of own vehicle MC can be improved.

The calculator 325 calculates the distance, relative speed and angle (azimuth) to the target based on the peaks extracted by the peak extractor 324 .

Specifically, the calculation unit 325 derives the distance and relative speed to the target based on the combination of the peak distance bins and speed bins extracted by the peak extraction unit 324 .

Further, the calculation unit 325 estimates the angle of the target by predetermined angle calculation processing. Specifically, the calculation unit 325 estimates the angle of the target based on the difference in phase between the peaks of the same distance bins of the frequency spectra of the four beat signals SB based on the reception signals SR of the four reception antennas 21a to 21d. . Note that when it is detected that a plurality of targets exist in the same distance bin due to differences in the phases of the peaks of the same distance bin, angle estimation is performed for each of the plurality of targets.

Note that the angle estimation in the calculation unit 325 is performed using a predetermined estimation method such as ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques), DBF (Digital Beam Forming), or MUSIC (Multiple Signal Classification). .

The output unit 326 outputs target information to the vehicle control device 2 . For example, the output unit 326 outputs the distance, relative speed, and angle of the detected target to the vehicle control device 2 as target information.

Also, the output unit 326 may output the determination result of the determination unit 323 as the target object information. In other words, the output unit 326 outputs the type information, which is the result of determination, separation/approach, before overtaking/after overtaking, etc., as target object information.

Next, a processing procedure of determination processing executed by the radar device 1 according to the embodiment will be described with reference to FIG. 8 . FIG. 8 is a flow chart showing the procedure of determination processing executed by the radar device 1 .

First, as shown in FIG. 8, the generator 321 performs frequency analysis on a beat signal obtained by mixing a frequency-modulated transmission wave (chirp wave) and a reflected wave of the transmission wave from a target. Thus, a two-dimensional frequency spectrum is generated in the distance direction and the relative velocity direction (step S101).

Subsequently, the determination unit 323 compares the generated peak distribution of the two-dimensional frequency spectrum with the distribution model, which is the model information 331 (step S102).

As a result of the comparison, the determination unit 323 determines whether the peak distribution and the distribution model are similar (step S103). When determining that the distribution model is similar (step S103, Yes), the determining unit 323 determines that the peak distribution is the target type corresponding to the distribution model (step S104).

Further, the determination unit 323 determines whether or not the peak distribution spreads in the relative velocity direction (the velocity bin direction) (step S105). If the determination unit 323 determines that the peak distribution spreads in the relative velocity direction (speed bin direction) (step S105, Yes), it determines whether the spread is in the positive relative velocity direction (step S106). ).

If the spread is in the positive speed direction (step S106, Yes), the determination unit 323 determines that the peak distribution is a target that separates from the own vehicle MC (step S107), and ends the process. .

On the other hand, in step S103, when the peak distribution and the distribution model are not similar (step S103, No), the determination unit 323 terminates the process.

Further, in step S105, when the peak distribution does not spread in the speed direction (step S105, No), the determination unit 323 determines that the target is at the same speed as the own vehicle MC (step S109), and the process is continued. finish.

Further, in step S106, when the spread of the peak distribution is in the negative relative velocity direction (step S106, No), the determination unit 323 determines that the peak distribution is a target approaching the own vehicle MC. (step S108), and the process ends.

As described above, the radar device 1 according to the embodiment includes the generator 321 and the determiner 323 . The generation unit 321 performs frequency analysis on the beat signal obtained by mixing the frequency-modulated transmission wave and the reflected wave of the transmission wave from the target, thereby generating a two-dimensional frequency in the distance direction and the relative velocity direction. Generate a spectrum. The determination unit 323 determines the target type based on the spread in the distance direction of the peak distribution in the two-dimensional frequency spectrum generated by the generation unit 321 . As a result, the type of target can be determined early.

In the above-described embodiment, all of the plurality of chirp waves Ch of the transmission wave SW show a case where the frequencies continuously increase (that is, up-chirp), but for example, the frequencies continuously decrease (that is, , down chirp) may be a chirp wave Ch.

Further effects and modifications can be easily derived by those skilled in the art. Therefore, the broader aspects of the invention are not limited to the specific details and representative embodiments so shown and described. Accordingly, various changes may be made without departing from the spirit or scope of the general inventive concept defined by the appended claims and equivalents thereof.

Reference Signs List 1 radar device 2 vehicle control device 10 transmission unit 11 signal generation unit 12 oscillator 13 transmission antenna 20 reception unit 21, 21a to 21d reception antenna 22, 22a to 22d mixer 23, 23a to 23d A/D converter 30 processing unit 31 transmission Control unit 32 Signal processing unit 33 Storage unit 321 Generation unit 322 Map generation unit 323 Determination unit 324 Peak extraction unit 325 Calculation unit 326 Output unit 331 Model information 100 Radar device MC Vehicle P Target S Radar system

Claims (5)

Frequency analysis is performed on the beat signal obtained by mixing the frequency-modulated transmitted wave and the reflected wave of the transmitted wave from the target to generate a two-dimensional frequency spectrum in the direction of distance and relative velocity. a generator;
a determination unit that determines the type of the target based on the spread in the distance direction of the peak distribution in the two-dimensional frequency spectrum generated by the generation unit ;
The determination unit is
Further determining whether the target is approaching or leaving the vehicle based on the spread of the peak distribution in the relative velocity direction.
A target detection device characterized by: The determination unit is
The target detection device according to claim 1 , wherein it is determined whether the target is before or after overtaking the own vehicle based on the distortion of the peak distribution in the relative velocity direction. A storage unit that stores model information indicating a distribution model of the peak distribution corresponding to the type of the target,
The determination unit is
3. The type of the target is determined by comparing the distribution model in the model information and the peak distribution in the two -dimensional frequency spectrum generated by the generator. The target object detection device according to . further comprising a map generation unit that generates map information mapping the peak distribution based on the two-dimensional frequency spectrum generated by the generation unit;
The determination unit is
The target detection device according to any one of claims 1 to 3 , wherein the type of the target is determined based on the map information generated by the map generation unit. A target detection method in which a radar device detects a target,
Frequency analysis is performed on the beat signal obtained by mixing the frequency-modulated transmitted wave and the reflected wave of the transmitted wave from the target to generate a two-dimensional frequency spectrum in the direction of distance and relative velocity. a production process;
a determination step of determining the type of the target based on the spread in the distance direction of the peak distribution in the two-dimensional frequency spectrum generated by the generation step;
with
The determination step includes
Further determining whether the target approaches or leaves the vehicle based on the spread of the peak distribution in the relative velocity direction,
A target object detection method characterized by:

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