JP2001324566A - Fm-cw radar device and target detecting method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an FM-CW radar device and a target detecting method that can reduce misidentification in various road environments and reduce the maximum load on a microprocessor for signal processing. SOLUTION: The FM-CW radar device has a means for detecting spectrum distribution and, depending on the detected spectrum distribution, detecting an irregular stationary object detection range wherein an irregular stationary object is present, and a means for calculating a temporary threshold depending on peak level distribution in the irregular stationary object detection range, and detecting and removing a peak presumed an irregular stationary object.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to a triangular wave FM.
FM-CW (Frequenc) using a continuous wave of modulated waves
y Modulation-Continuous W
The present invention relates to an ave (frequency modulation-continuous wave) radar technology, and more particularly to an FM-CW radar device and a target detection method capable of reducing erroneous recognition in various road environments and reducing a maximum load on a microprocessor executing signal processing.

[0002]

2. Description of the Related Art Conventionally, an on-vehicle radar device mounted on an automobile or the like can monitor other automobiles traveling in front and behind to simultaneously measure a distance and a relative speed.
In particular, technology for monitoring a vehicle traveling ahead is important for preventing a rear-end collision or a collision accident of the vehicle, and is expected to be greatly useful in the future. As such an on-vehicle radar device, there is, for example, a millimeter wave radar device that applies radio waves in the millimeter wave band. As a typical system of the millimeter wave radar device, for example, there is an FM-CW radar device using a continuous wave of an FM modulation wave by a triangular wave.

[0003] In the FM-CW radar apparatus, a continuous wave FM-modulated by a triangular wave is transmitted as a transmission wave to a target such as an automobile or an obstacle located in front of the radar, and the reflected light is reflected by the target and returned. A beat signal obtained by mixing the transmitted wave and the received wave at this time is adopted as a received wave, for example, by FFT (F
Signal processing is performed by a frequency analysis method such as ast Fourier Transform (fast Fourier transform) to calculate a target observation position and a relative velocity.

[0004] At this time, the distance to the target and the relative velocity are calculated by the following equations by combining the spectrum peaks fa and fb of the up section and the down section modulated by the triangular wave for each moving object (target).

Distance R = A · ((fa + fb) / 2) (A: constant) Relative speed V = A · ((fa−fb) / 2) (A: constant) At this time, each moving object (target) In peak pairing (peak pairing), for example, after narrowing down the combination candidates by the relative speed upper limit value to be detected, the movement trajectory estimated from each combination candidate and the actual trajectory are compared in a time series, and the combination is performed. A combination indicating a target is detected from the candidates.

[0006]

However, in the conventional FM-CW radar device, when a target automobile runs along a road structure called a continuous stationary object such as a soundproof wall or a tunnel, or when a target vehicle runs along a roadside. For example, when a car travels in an urban area where a large number of stationary objects are randomly present, the total number of spectrum peaks is very large, and the position at which the spectrum peak is detected is mainly random due to the continuity of the reflective surface. However, in the method such as the peak pairing described above, a large number of spectrum positions are changed at random in a time-series determination, and thus an incorrect combination candidate is detected as a moving object (target). There was a point.

The present invention has been made in view of the above problems, and has as its object to reduce erroneous recognition in various road environments and reduce the maximum load on a microprocessor that executes signal processing. An object of the present invention is to provide a possible FM-CW radar device and a target detection method.

[0008]

The gist of the present invention is that a spectrum distribution state is detected, and a range in which an irregular stationary object is generated based on the detected spectrum distribution state. And a means for calculating a temporary threshold based on the peak level distribution of the irregular stationary object detection range and detecting and removing a peak considered to be an irregular stationary object. The present invention resides in an FM-CW radar device. The gist of the invention according to claim 2 of the present invention is that a radar head is provided with a transmission / reception antenna, and from the transmission / reception antenna, an FM modulated wave FM-modulated by a triangular wave is transmitted toward a target such as an automobile, The reflected wave reflected by the target is received by the transmitting / receiving antenna, and the reflected wave reflected by the target is received by the transmitting / receiving antenna, and then mixed with the transmitted wave to form a beat signal, and the beat signal is a low-pass filter. , An amplifier, an A / D converter, and sent to a microprocessor in digital signal form, wherein the microprocessor comprises:
A frequency analysis processor, a target recognizer, a target follower, and a danger discriminator, wherein the frequency analysis processor is based on discrete value data of a beat signal sampled at a fixed time using the A / D converter. Has a function of extracting a spectrum related to the target by using a predetermined frequency component analysis method, and the target recognizer detects a peak frequency based on the spectrum extracted by the frequency analysis processor, and detects a peak frequency of the target. It has a function of calculating the observation position and the relative speed, the target follower has a function of estimating the target position of the next cycle based on the target calculated by the target recognizer and updating the target recognition, The danger classifier is based on the smooth position and the relative speed of the target obtained by the target follower, based on the target It consists in the FM-CW radar apparatus characterized by having a function of discriminating the Kendo. The gist of the invention according to claim 3 of the present invention is that the target follower has a function of calculating a smooth position from an observed position and an estimated position of the target. Exists in CW radar equipment. The gist of the invention described in claim 4 of the present invention is that the frequency analysis processor uses FFT based on discrete value data of a beat signal sampled at a fixed time using the A / D converter. 3. The FM-CW according to claim 2, further comprising a function of extracting a spectrum related to the target.
Present in radar equipment. The gist of the invention described in claim 5 of the present invention is to have an alarm device that warns the driver using an alarm display or an alarm sound based on the degree of danger determined by the danger classifier. The FM-CW radar device according to any one of claims 2 to 4, wherein: The gist of the invention described in claim 6 of the present invention is that an irregular stationary object detection range which is a range in which an irregular stationary object is generated is detected based on the detected spectrum distribution state. And detecting a peak considered to be an irregular stationary object by calculating a temporary threshold based on the peak level distribution of the irregular stationary object detection range, and removing the peak. Exists. The gist of the invention described in claim 7 of the present invention is that the radar head is provided with a transmission / reception antenna, and the transmission / reception antenna outputs the FM by a triangular wave.
A modulated FM modulated wave is transmitted toward a target such as an automobile, and a reflected wave reflected by the target is received by the transmitting / receiving antenna, and a reflected wave reflected by the target is received by the transmitting / receiving antenna, It is mixed with the transmitted wave to become a beat signal,
The beat signal is a low-pass filter, a signal amplification process,
Sent to a means for performing a target detection process in the form of a digital signal via an A / D conversion process, wherein the target detection process includes a frequency analysis process, a target recognition process, a target following process, and a danger determination process; Includes a step of extracting a spectrum related to a target using a predetermined frequency component analysis method based on discrete value data of a beat signal sampled at a fixed time using the A / D conversion processing, The target recognition processing includes a step of detecting a peak frequency based on the spectrum extracted in the frequency analysis processing to calculate a target observation position and a relative speed, and the target tracking processing is performed by the target recognition processing. Of updating the target recognition by estimating the target position of the next cycle based on the obtained target Has the danger determination process, based on the smoothed position and the relative velocity of the target obtained by the target tracking process, resides in target detection method characterized by comprising the step of determining the risk for the target. The gist of the invention described in claim 8 of the present invention is that the target following processing has a step of calculating a smooth position from an observed position and an estimated position of the target. Be in the way. The gist of the invention described in claim 9 of the present invention is that the frequency analysis processing uses FFT based on discrete value data of a beat signal sampled at a fixed time using the A / D conversion processing. Extracting a spectrum associated with the target.
In the method for detecting a target described in 1. above. The gist of the invention described in claim 10 of the present invention is to have an alarm process for giving an alarm to the driver using an alarm display or an alarm sound based on the degree of danger determined by the danger determination process. The target detection method according to any one of claims 7 to 9, characterized in that: The gist of the invention according to claim 11 of the present invention resides in that the target recognition processing includes a detection module for all peaks of a spectrum, an irregular stationary object range detection module, an irregular stationary object peak removal module, a peak pairing module, and a target. Executing a position / velocity calculation module, in the detection module for all spectrum peaks, in order to detect all peaks in the ascending section and the descending section, extract a spectrum peak having a peak level exceeding a predetermined standard threshold, In the irregular stationary object range detection module, in order to detect the irregular stationary object detection range, first, in the arbitrary detection range, determine whether the total number of peaks is greater than a predetermined peak total threshold, If the total number of peaks is greater than the peak total number threshold, In the detection range, it is determined whether or not the spectrum integration value is larger than a predetermined spectrum integration value threshold, and if the spectrum integration value is larger than the spectrum integration value threshold, the arbitrary detection range is regarded as an irregular detection range. Further, the same detection is performed by shifting the arbitrary detection range by a predetermined displacement, and after examining the entire radar detection range, the entire range determined as the irregular detection range is set as the irregular stationary object detection range, In the irregular stationary object peak removal module, in order to perform peak removal by the irregular stationary object, to determine a peak level average value for the irregular stationary object detection range obtained by using the irregular stationary object range detection module, Further, a peak level dispersion value is obtained for the irregular stationary object detection range, and the obtained peak level flat value is obtained. A temporary threshold is calculated based on the value and the peak level dispersion value, and a peak position exceeding the temporary threshold is extracted in the irregular stationary object detection range, and the peak pairing module uses an irregular stationary object from all peaks. The peak pairing is performed using the remaining peaks excluding the peak, and the target position / velocity calculation module performs the position and relative position of the target based on the peak pairing result of the target obtained by the peak pairing module. The target detection method according to any one of claims 7 to 10, wherein the speed is calculated.

[0009]

DESCRIPTION OF THE PREFERRED EMBODIMENTS The FM-CW radar device of the present invention is directed toward a target such as an automobile located in front of the radar.
A continuous wave FM-modulated by a triangular wave is transmitted as a transmission wave, a reflected wave reflected by the target and returned is taken in as a reception wave, and a beat signal obtained by mixing the transmission wave and the reception wave at this time is expressed by: For example, FFT
By performing signal processing using a frequency analysis method such as
The distance to the target and the relative speed can be calculated.

In the detection of a target in an FM-CW radar apparatus using a millimeter wave band, a spectrum peak exceeding a predetermined standard threshold based on an up-spectrum spectrum and a down-spectrum spectrum is regarded as reflection from the target. Thus, the peak pairing process of the upper and lower sections is executed. The standard threshold value is generally calculated by measuring a noise level in a situation where a target does not exist and adding a certain margin to the measured value. However, in an actual field, a spectrum of many targets existing in addition to the preceding vehicle appears. Particularly, on a soundproof wall, a tunnel, or an urban area seen on a highway or the like, a continuous irregular stationary object is detected and appears randomly on the spectrum. The spectrum appearing at random has no regularity even between cycles, and it is difficult to catch it as a stationary object. That is, in the conventional setting method based on the standard threshold, a large number of peaks are detected, and since the large number of peaks occur at random positions between cycles, there is a possibility that an incorrect peak pair is calculated by the pairing process. However, there is a problem that the target is erroneously recognized. In addition, since the peak pairing processing time is largely affected by a large number of peaks caused by an irregular stationary object, the load on the microprocessor may be increased.

An object of the present invention is to reduce misrecognition in various road environments and to reduce the maximum load on a microprocessor that executes signal processing. Based on the detected spectrum distribution state, a range where an irregular stationary object is generated (irregular stationary object detection range) is detected, and a temporary threshold is set based on the peak level distribution of the irregular stationary object detection range Wrp. Is calculated to detect and remove peaks that are considered to be irregular stationary objects. As a result, at the same time as detecting a true moving object (target),
There is an effect that the total number Npk of peaks of the irregular stationary object can be reduced. Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

FIG. 1 is a block diagram of an FM- according to an embodiment of the present invention.
FIG. 2 is a functional block diagram for explaining the CW radar device 10. In FIG. 1, 1 is a radar head, 2 is a low-pass filter (LPF), 3 is an amplifier, 4 is an A / D converter,
5 is a microprocessor, 51 is a frequency analysis processor, 5
2 is a target recognizer, 53 is a target follower, 54
Is a danger classifier, 6 is an alarm, and 10 is an FM of the present embodiment.
2 shows a CW radar device.

An embodiment of the present invention will be described with reference to the drawings. First, referring to FIG. 1, an overall configuration of an FM-CW radar device 10 according to one embodiment of the present invention is shown. Referring to FIG. 1, the FM of the present embodiment
The CW radar device 10 has a function of detecting the distance to the target and the relative speed to the target by using a radio signal. The radar head 1 is provided with a transmitting / receiving antenna 7, and the transmitting / receiving antenna 7 outputs a triangular wave. The FM-modulated wave subjected to FM modulation is transmitted toward a target such as an automobile, and the reflected wave reflected by the target is received by the transmission / reception antenna 7.

After the reflected wave reflected by the target is received by the transmitting / receiving antenna 7, it is mixed with the transmitted wave in the radar head 1 to become a beat signal.
The beat signal is sent to the microprocessor 5 in the form of a digital signal via the low-pass filter 2 (LPF), the amplifier 3, and the A / D converter 4.

The microprocessor 5 includes a frequency analysis processor 51, a target recognizer 52, and a target follower 53.
And a danger classifier 54.

The frequency analysis processor 51 includes an A / D converter 4
FFT (Fast Fourier) based on discrete value data of a beat signal sampled at a certain time using
A spectrum related to the target is extracted by using a frequency component analysis technique such as Transform.

The target recognizer 52 detects the peak frequency based on the spectrum extracted by the frequency analysis processor 51, and calculates the target observation position and the relative speed.

The target follower 53 updates the target recognition by estimating the target position of the next cycle of the microprocessor 5 based on the target calculated by the target recognizer 52. Further, a smooth position is calculated from the target observation position and the estimated position.

The danger classifier 54 includes a target follower 53
Is determined based on the smooth position of the target obtained in step (1) and the relative speed obtained by the target recognizer 52 (in other words, whether the risk to the host vehicle is high).

The alarm 6 warns the driver based on the degree of danger determined by the danger classifier 54 using an alarm display or an alarm sound.

Next, the operation (target detection method) of the FM-CW radar device 10 will be described. First, the operation principle of the microprocessor 5 of FIG. 1 will be described with reference to FIG. FIG. 2 is a flowchart for explaining a target detection method according to one embodiment of the present invention.

The microprocessor 5 performs main routines, namely, initialization (step S1), frequency analysis processing (step S2), target recognition processing (step S3), target following processing (step S4), and danger determination processing (step S5). In addition, it is supported by various operation programs.

The main routine includes steps S1 to S5 as shown in the flowchart of FIG.

In the present embodiment, first, when the operation of turning on the power by operating the ignition key is performed to operate the engine of the automobile, the reset of the microprocessor 5 is released after a lapse of a predetermined time. Upon reset release, the microprocessor 5 is started and executes the program from a predetermined address (usually, zero address).

The main routine will be described with reference to FIGS. First, initialization (step S1)
In, initialization is performed, and various variables are initialized.

When the frequency analysis processing (step S2) is executed following step S1, the transmission wave transmitted from the radar head 1 is reflected on the target and returns as a reception wave, and a beat signal is generated based on the reception wave. Generated. At the same time that the radio wave frequency-modulated by the triangular wave is output,
A / D conversion of the beat signal is started. The discrete data of the beat signal is stored in the microprocessor 5 one by one.
Is stored inside. In addition, since the A / D conversion is performed at a constant sampling time, a timer interrupt or the like is generally used for monitoring the sampling time. Discrete conversion of the beat signal by the A / D converter 4 is executed for one cycle of the triangular wave. At this point, the discrete value data of the beat signal corresponding to the rising section and the falling section of the triangular wave has been accumulated in the microprocessor 5. FFT (Fast Four) based on discrete value data of a beat signal corresponding to the rising section and the falling section of the triangular wave.
A discrete spectrum of each section can be obtained by using a frequency analysis method represented by the “Ier Transform” or the like.

In the target recognition process (step S3), based on the discrete spectrum obtained in step S2, a combination of peaks in an up section and a down section is obtained to detect an observation position and a relative speed.

In the target following process (step S4), based on the target observation position obtained in step S3, the target following process is performed according to the vehicle motion state, and the target smooth position is obtained.

In the danger determination process (step S5), based on the smooth position and the relative speed obtained in step S4,
The degree of danger to the own vehicle is determined. If it is determined that the risk is high, the driver is alerted by displaying an alarm. After the end of step S5, the process jumps to step S2, where steps S2, S3, S4,
Step S5 is looped.

The target recognizer 52 which is the subject of the present proposal
This will be described in detail with reference to FIGS. 3, 4, 5, and 6. FIG. FIG. 3 is a flowchart for explaining a target recognition process in the target detection method of FIG. 2. FIG. 4 is a flowchart showing a process of detecting a target stationary still object removal executed by the irregular stationary object range detection module in the target recognition process of FIG. FIG. 5 is a flowchart for explaining, and FIG.
Is a flowchart for explaining a process of removing a target irregular stationary object performed by the irregular stationary object peak removal module in the target recognition process of FIG. 6, FIG. 6 is a graph showing a spectrum at the time of normal detection, and FIG. FIG. 8 is a graph showing an irregular reflection spectrum according to FIG. 8, FIG. 8 is a graph for explaining an irregular stationary object detection range Wrp, and FIG.
9 is a graph for explaining a process of removing irregular stationary object peaks.

As shown in FIG. 3, the target recognizer 52
The target recognition process executed by the module includes a spectrum full peak detection module (step S10), an irregular stationary object range detection module (step S11), an irregular stationary object peak removal module (step S12), and a peak pairing module (step S13). ), Execute the target position / velocity calculation module (step S14).

The spectrum peak detection module (step S10) detects all peaks in the up section and the down section. The target recognizer 52 extracts a spectrum peak having a peak level exceeding a predetermined standard threshold, as shown in FIG. 6, in order to detect all the peaks.

In the irregular stationary object range detection module (step S11), first, in order to detect the irregular stationary object detection range Wrp, the total number N of peaks in the arbitrary detection range Wpk is first determined.
It is determined whether or not pk is greater than a predetermined peak total threshold Npkth. When the total number of peaks Npk is larger than the total number of peaks threshold Npkth, it is determined whether or not the spectrum integration value Ipk is larger than a predetermined spectrum integration value threshold Ipkth in the arbitrary detection range Wpk. When the spectrum integral value Ipk is larger than the spectrum integral value threshold value Ipkth, the arbitrary detection range Wpk is set as the irregular detection range. Further, as the displacement ΔR, the arbitrary detection range Wpk
To perform the same detection. After checking the entire radar detection range, the entire range determined as the irregular detection range is set as the irregular stationary object detection range Wrp.

Here, the irregular stationary object range detection module (step S11) will be described with reference to the flowchart of FIG. In the present embodiment, first, it is checked in step S20 whether the evaluation of the up section has been completed. If the evaluation of the up section has been completed (Y in step S20), the process proceeds to step S21. If the evaluation of the up section has not been completed (N in step S20), the process proceeds to step S22.

In step S21, it is checked whether or not the evaluation of the down section has been completed. If the evaluation of the down section has been completed (Y in step S21), the irregular still object range detection module is completed (module processing is completed), and the process returns. If the evaluation has not been completed (N in step S21), the process proceeds to step S22.

In step S22, as shown in FIG.
Random detection range Wpk from distance R Irregular stationary object detection range Wrp
Is determined. The initial value of the distance R that defines the irregular stationary object detection range Wrp is set to 0 (initialized to R = 0).

In step S23, it is checked whether or not the arbitrary detection range Wpk determined in step S22 is larger than the radar detection range. If the arbitrary detection range Wpk is smaller than the radar detection range (<of step S23), the process proceeds to step S25. On the other hand, if the arbitrary detection range Wpk is larger than the radar detection range (≧ in step S23), the process proceeds to step S24.

In step S25, the entire range determined as the detection range of the irregular stationary object is replaced with the entire range of the irregular stationary object detection.
That is, the irregular stationary object detection range Wrp is set. Here, after determining whether or not the random detection range Wpk moving for each displacement ΔR is a range in which an irregular stationary object is occurring, a portion where each of the random detection ranges Wpk overlaps is irregularly defined in an up section or a down section. It is assumed that all sections in which a stationary object is detected.

Then, the process proceeds to step S20 to check whether or not the evaluation of the upper and lower sections has been completed.

In step S24, the total number Npk of peaks in the arbitrary detection range Wpk is calculated. This peak total number Npk
Can usually be calculated as a spectrum peak exceeding a predetermined standard threshold. In general, the standard threshold value is often set by adding a certain value to the spectrum amplitude when no target is present ahead.

In step S26, it is determined whether or not the total number of peaks Npk calculated in step S24 exceeds the total number of peaks threshold Npkth. Here, the arbitrary detection range Wpk
By examining the total number Npk of peaks, it is determined whether there is a high possibility that an irregular stationary object exists in the arbitrary detection range Wpk. Therefore, when the total number of peaks Npk is equal to or smaller than the total number of peaks threshold Npkth (≦ in step S26), it is determined that the possibility of occurrence of the irregular stationary object is low and the process proceeds to step S20. On the other hand, when the total number of peaks Npk exceeds the total number of peaks threshold Npkth (> in step S26), it is determined that there is a high possibility that an irregular stationary object has occurred in the same range, and the process proceeds to step S27.

In step S27, a spectrum integral value Ipk in the arbitrary detection range Wpk is calculated. The feature of the section in which the irregular stationary object occurs is that not only the existence of a large number of peaks but also the continuous distribution of the spectrum. This is clearly different from the spectrum distribution when cars are running in a row.

In step S28 following step S27, the spectrum integrated value Ip calculated in step S27 is obtained.
It is determined whether or not k exceeds the spectrum integration value threshold value Ipkth. If the spectrum integral value Ipk is equal to or smaller than the spectrum integral value threshold value Ipkth (≦ in step S28),
Although many peaks occur, it is determined that the object is not an irregular stationary object, and the process proceeds to step S20. On the other hand, when the spectrum integral value Ipk exceeds the spectrum integral value threshold value Ipkth (> in step S28), the process proceeds to step S29.

In step S29, it is determined that the arbitrary detection range Wpk is a range where irregular stationary objects are generated (irregular detection range). When an irregular stationary object is generated, a large number of peaks are detected, and at the same time, the spectrum distribution becomes a continuous state with no boundaries. . The irregular stationary object range detection module (step S11) is characterized by capturing and recognizing the detection state of such an irregular stationary object.

In step S30, the detection range is updated by displacing the arbitrary detection range Wpk by a displacement ΔR as R = R + ΔR.

Next, in the irregular stationary object peak removal module (step S12), as shown in the flowchart of FIG. 5, an irregular stationary object range detection module (step S12) is used to execute peak removal by the irregular stationary object. S1
The peak level average value AVEpk is obtained for the irregular stationary object detection range Wrp obtained using 1). Further, a peak level dispersion value σpk is determined for the irregular stationary object detection range Wrp. A temporary threshold is calculated based on the obtained peak level average value AVEpk and peak level variance σpk.

Here, LVL (σpk) is a coefficient for correcting the temporary threshold according to the degree of variation of each peak level LVLpk with respect to the average peak level AVEpk. This makes it possible to perform detection and removal in a form suitable for the distribution state of the irregular stationary object, and the irregular stationary object detection range
In Wrp, it becomes possible to extract a peak whose peak level LVLpk is larger than the temporary threshold.

Next, the irregular stationary object peak removal module (step S12) will be described with reference to the flowchart of FIG. In the present embodiment, first, it is determined whether or not the evaluation of the up section has been completed in step S40. If the evaluation of the up section has been completed (Y in step S40), the process proceeds to step S41. If the evaluation of the up section has not been completed (N in step S40), the process proceeds to step S42.

In step S41, it is checked whether or not the evaluation of the down section has been completed. If the evaluation of the down section has been completed (Y in step S41), the irregular stationary object peak removal module is completed (module processing is completed), and the process returns. If the evaluation has not been completed (N in step S41), the process proceeds to step S42.

In step S42, each peak level average value AVEpk is calculated for the irregular stationary object detection range Wrp obtained by the irregular stationary object range detection module (step S11).

In step S43, each peak level dispersion value σpk is calculated for the irregular stationary object detection range Wrp obtained by the irregular stationary object range detection module (step S11).

In step S44, a temporary threshold in the irregular stationary object detection range Wrp is obtained according to the following equation.

Temporary threshold = AVEpk + LVL (σpk) LVL (σpk) = k * σ (k: constant) FIG. 7 shows how the temporary threshold is set for the irregular stationary object detection range Wrp using the above equation. I have.

In step S45, as shown in FIG.
The peak is extracted again based on the temporary threshold value obtained in step S44. In the extraction of the peak again, the peak of the moving object (target) from which the peak spectrum caused by the irregular stationary object has been removed based on all the peak spectra extracted previously by selecting the peak spectrum exceeding the temporary threshold value Get the spectrum.

After the end of step S45, step S40
Returning to step S3, the completion of the evaluation of the up section is checked. If the evaluation is completed (Y in step S40), the completion of the evaluation of the down section is checked in step S41.
41) Irregular stationary object peak removal module (step S12) is completed and returns.

The peak pairing module (step S
In 13), peak pairing is performed using the remaining peaks excluding the peaks due to the irregular stationary object from all the peaks. Peak pairing (peak pairing) for each moving object (target) is performed, for example, by narrowing down the combination candidates based on the detected relative speed upper limit value, and then moving the movement trajectory estimated from each combination candidate in time series with the actual movement trajectory. By comparing the trajectories, the combination indicating the target is detected from the combination candidates.

The target position / velocity calculation module (step S14) calculates the position and relative speed of the moving object (target) based on the peak pairing result of the moving object (target) obtained in step S13.

It should be noted that the present invention is not limited to the above embodiment, and it is apparent that the above embodiment can be appropriately modified within the scope of the technical idea of the present invention. Further, the number, position, shape, and the like of the constituent members are not limited to the above-described embodiment, and can be set to numbers, positions, shapes, and the like suitable for carrying out the present invention. In each drawing, the same components are denoted by the same reference numerals.

[0059]

Since the present invention is configured as described above, when the target vehicle travels along a road structure called a continuous stationary object such as a soundproof wall or a tunnel, or when an emergency is placed on the side of the road. For example, when traveling in an urban area where many stationary objects are randomly present, the threshold is temporarily replaced by using a means for detecting a continuous stationary object existing on the side of the road and calculating the peak of the target. , The number of detected peaks can be reduced. Thus, by detecting a moving object (target) by removing a continuous stationary object, detection of an erroneous target in peak pairing can be prevented. Further, by removing continuous stationary objects, the calculation load required for target detection can be suppressed to a certain value or less without being affected by the road environment.
This makes it possible to keep the target detection cycle time constant.

As a result, the detection of an erroneous target can be minimized, and the target can be detected at regular time intervals. It has the effect of being able to execute.

[Brief description of the drawings]

FIG. 1 is a functional block diagram for explaining an FM-CW radar device according to an embodiment of the present invention.

FIG. 2 is a flowchart illustrating a target detection method according to an embodiment of the present invention.

FIG. 3 is a flowchart illustrating a target recognition process in the target detection method of FIG. 2;

FIG. 4 is a flowchart for explaining an irregular stationary object range detection module in the target recognition processing of FIG. 3;

FIG. 5 is a flowchart for explaining an irregular stationary object peak removal module in the target recognition processing of FIG. 3;

FIG. 6 is a graph showing a spectrum at the time of normal detection.

FIG. 7 is a graph showing an irregular reflection spectrum due to a roadside soundproofing wall and the like.

FIG. 8 is a graph for explaining an irregular stationary object detection range.

FIG. 9 is a graph for explaining a process of removing irregular stationary object peaks.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 ... Radar head 2 ... Low pass filter (LPF) 3 ... Amplifier 4 ... A / D converter 5 ... Microprocessor 6 ... Alarm 7 ... Transceiver antenna 10 ... FM-CW radar device 51 ... Frequency analysis processor 52 ... Target recognition Instrument 53 ... Target follower 54 ... Danger classifier

Claims (11)

[Claims] 1. A means for detecting a spectrum distribution state, and detecting an irregular stationary object detection range in which an irregular stationary object is generated, based on the detected spectrum distribution state; F. means for calculating a temporary threshold based on the peak level distribution of the object detection range to detect and remove peaks considered to be irregular stationary objects.
M-CW radar device. 2. A radar head is provided with a transmitting / receiving antenna, from which an FM-modulated wave FM-modulated by a triangular wave is transmitted toward a target such as an automobile, and a reflected wave reflected by the target is transmitted. The reflected wave received by the transmission / reception antenna and reflected by the target is received by the transmission / reception antenna, and then mixed with the transmission wave to form a beat signal. The beat signal passes through a low-pass filter, an amplifier, and an A / D converter. The digital signal is sent to a microprocessor in the form of a digital signal. The microprocessor includes a frequency analysis processor, a target recognizer, a target follower, and a danger discriminator, and the frequency analysis processor uses the A / D converter. Based on the discrete value data of the beat signal The target recognizer has a function of extracting a spectrum related to the target by using a predetermined frequency component analysis method, and the target recognizer detects a peak frequency based on the spectrum extracted by the frequency analysis processor to observe the target. The target follower has a function of estimating a target position of the next cycle based on the target calculated by the target recognizer and updating the target recognition, and The danger classifier has a function of judging the degree of danger to the target based on the smooth position and relative speed of the target obtained by the target follower, wherein the danger classifier has a function of judging the degree of danger to the target. 3. The FM-CW radar device according to claim 2, wherein the target follower has a function of calculating a smooth position from the observed position and the estimated position of the target. 4. The frequency analysis processor extracts a spectrum related to a target using FFT based on discrete value data of a beat signal sampled at a fixed time using the A / D converter. The FM-CW radar device according to claim 2, having a function. 5. The apparatus according to claim 2, further comprising an alarm device that warns the driver using an alarm display or an alarm sound based on the degree of danger determined by the danger classifier. The FM-CW radar device according to claim 1. 6. A step of detecting a spectrum distribution state and detecting an irregular stationary object detection range in which an irregular stationary object is generated, based on the detected spectrum distribution state; A target detection method comprising: calculating a temporary threshold based on a peak level distribution of an object detection range to detect and remove a peak considered to be an irregular stationary object. 7. A radar head is provided with a transmission / reception antenna, from which an FM-modulated wave FM-modulated by a triangular wave is transmitted toward a target such as an automobile, and a reflected wave reflected by the target is transmitted. The reflected wave received by the transmission / reception antenna and reflected by the target is received by the transmission / reception antenna, and then mixed with the transmission wave to form a beat signal. The beat signal is subjected to a low-pass filter, signal amplification processing, A
The target detection processing is sent to a unit that performs target detection processing in the form of a digital signal via a / D conversion processing, and the target detection processing includes a frequency analysis processing, a target recognition processing, a target following processing, and a danger determination processing. Extracting a spectrum related to a target using a predetermined frequency component analysis method based on discrete value data of a beat signal sampled at a fixed time using the A / D conversion processing, The target recognition processing includes a step of detecting a peak frequency based on the spectrum extracted in the frequency analysis processing to calculate a target observation position and a relative speed, and the target following processing is calculated by the target recognition processing. The process of estimating the target position in the next cycle based on the target and updating the target recognition And a danger determination process including a step of determining a degree of danger to the target based on a smooth position and a relative speed of the target obtained in the target following process. 8. The target detection method according to claim 7, wherein the target following processing has a step of calculating a smooth position from an observed position and an estimated position of the target. 9. The frequency analysis processing is a step of extracting a spectrum related to a target using FFT based on discrete value data of a beat signal sampled at a fixed time using the A / D conversion processing. The target detection method according to claim 7, comprising: 10. The apparatus according to claim 7, further comprising an alarm process for warning a driver using an alarm display or an alarm sound based on the degree of danger determined by the danger determination process. The target detection method according to claim 1. 11. The target recognition processing includes executing a spectrum full peak detection module, an irregular stationary object range detection module, an irregular stationary object peak removal module, a peak pairing module, and a target position / velocity calculation module. In the detection module of all spectrum peaks, in order to detect all peaks in the up section and the down section, extract a spectrum peak having a peak level exceeding a predetermined standard threshold, In the irregular stationary object range detection module, To detect the irregular stationary object detection range, first, in the arbitrary detection range, determine whether the total number of peaks is greater than a predetermined peak total number threshold, and if the total number of peaks is greater than the peak total number threshold In the arbitrary detection range, the spectrum It is determined whether or not the integrated value is larger than a predetermined spectrum integral value threshold. If the spectrum integral value is larger than the spectrum integral value threshold, the arbitrary detection range is set as an irregular detection range, and furthermore, only a predetermined displacement is set. The same detection is performed by shifting the arbitrary detection range, and after examining the entire radar detection range, the entire range determined as the irregular detection range is set as the irregular stationary object detection range, and the irregular stationary object peak is set. In the removal module, in order to execute peak removal by an irregular stationary object, a peak level average value is obtained for the irregular stationary object detection range obtained by using the irregular stationary object range detection module, and further, the irregular A peak level variance value is obtained for a stationary object detection range, and the obtained peak level average value and the peak level variance are obtained. A peak value exceeding the temporary threshold in the irregular stationary object detection range is extracted, and the peak pairing module removes the remaining peaks excluding the peaks due to the irregular stationary object from all peaks. The target position / velocity calculation module calculates the position and relative velocity of the target based on the peak pairing result of the target obtained by the peak pairing module. Claims 7 to 1
0. The target detection method according to any one of 0.