Target detection method and system, storage medium and electronic equipment

Abstract

The invention provides a target detection method and system, a storage medium and electronic equipment. The target detection method comprises the following steps: acquiring a distance Doppler spectrum of a detection radar, and performing initial target detection according to the distance Doppler spectrum to obtain a first detection target signal; performing channel separation on a transmitting channel of the detection radar based on the first detection target signal to obtain a second detection target signal; performing constant false alarm rate detection based on the second detection target signal to obtain a third detection target signal; and carrying out association matching on the secondary false target rejection result and the previous frame of target signal, so as to obtain a final detection target signal based on an association matching result and the third detection target signal. According to the invention, false target elimination can be realized under the condition of limited storage space or computing power resources, and weak and small target detection can be realized at the same time.

Description

Technical Field

[0001] The present application relates to the field of radar detection technology, and in particular to a target detection method, system, storage medium and electronic device. Background Art

[0002] Traditional automotive frequency-modulated continuous-wave millimeter-wave radars transmit a fixed center frequency of each chirp signal. Therefore, range resolution is determined by the bandwidth of a single chirp signal, or the bandwidth of the transmitted signal in the fast time dimension. However, due to performance and hardware limitations, existing automotive millimeter-wave radars cannot simultaneously achieve high range resolution, long detection range, and fast refresh cycles. Consequently, the range resolution of existing automotive millimeter-wave radars in long-range mode is typically low, with sparse data points. Frequency-modulated stepped-frequency radars, by varying the center frequency of each chirp signal, effectively achieve a large bandwidth in the slow time dimension, enabling higher range resolution in long-range mode. This advantage has made stepped-frequency radar a relatively new and popular waveform in automotive millimeter-wave radars.

[0003] However, due to the high energy of the transmitted waveform and the high range resolution required to achieve a wide detection range, echoes near strong targets can alias, potentially leading to errors in angle and velocity measurements by detection units near these targets, resulting in a certain number of false targets. Similarly, in this system, the coupling of target range and velocity can lead to strong sidelobes around strong targets, which can be detected by conventional target detection methods, resulting in false detection. Raising the detection threshold can lead to missed detection of weaker targets such as pedestrians. Summary of the Invention

[0004] In order to solve the above technical problems, the present application provides a target detection method, system, storage medium and electronic device.

[0005] Specifically, the present application provides a target detection method, comprising the following steps: obtaining a range Doppler spectrum of a detection radar, and performing initial target detection based on the range Doppler spectrum to obtain a first detection target signal; performing channel separation on the transmission channel of the detection radar based on the first detection target signal to complete a first false target elimination and obtain a second detection target signal; performing constant false alarm rate detection based on the second detection target signal to complete a second false target elimination and obtain a third detection target signal; and, correlating and matching the second false target elimination result with the target signal of the previous frame to obtain a final detection target signal based on the correlation matching result and the third detection target signal.

[0006] In the above technical solution, false target elimination is carried out in stages. By analyzing the signal characteristics of different transmission channels through channel separation, false targets caused by factors such as echo aliasing are identified and eliminated. Secondly, false targets caused by target distance coupling and other factors are further eliminated through constant false alarm rate detection. Furthermore, through correlation matching, accidental interference signals are eliminated, the accuracy and continuity of the target are improved, and the problem of missed detection of weak targets is effectively solved. It can be seen that this application can achieve false target elimination and weak target detection under the conditions of limited storage space / computing power resources.

[0007] Furthermore, the acquiring of the range Doppler spectrum of the detection radar includes: acquiring an echo signal based on a plurality of linear frequency modulation signals emitted by the detection radar; and performing fast Fourier transform on the echo signal based on the range dimension and the velocity dimension to acquire the range Doppler spectrum.

[0008] In the above technical solution, the linear frequency modulation signal is an important form of transmitting signal in the frequency-stepped frequency modulation radar. It has the advantage of being equivalent to a large bandwidth in the slow time dimension, which can improve the radar's range resolution; performing a fast Fourier transform in the distance dimension can convert the echo signal from the time domain to the frequency domain, thereby obtaining the target's distance information; performing a fast Fourier transform in the velocity dimension can obtain the target's velocity information. Through these two-step transformation, the range Doppler spectrum can be accurately constructed, intuitively displaying the target's distribution in the two dimensions of distance and velocity, and providing a clear data basis for subsequent target detection.

[0009] Furthermore, the obtaining of the first detected target signal includes: performing initial target detection on the range Doppler spectrum with a preset threshold value to obtain an echo signal with target energy greater than the preset threshold value as the first detected target signal.

[0010] In the above technical solution, echo signals with strong energy that may represent real targets can be quickly screened out, and some noise and interference signals with weaker energy can be preliminarily eliminated, thereby reducing the amount of data for subsequent processing and improving processing efficiency. At the same time, the preset threshold can be adjusted according to the actual application scenario, which has a certain degree of flexibility.

[0011] Furthermore, obtaining the second detection target signal includes: performing feature analysis based on the first detection target signal to obtain signal features; performing feature matching on the signal features with a preset feature template to assign the first detection target signal with successful feature matching to the corresponding channel; wherein, if the signal features fail to match the preset feature template features, the corresponding first detection target signal is eliminated, and the first detection target signal in each channel is used as the second detection target signal.

[0012] In the above technical solution, the preset feature template is pre-set based on the known target features; through feature matching, the first detection target signal can be assigned to the corresponding channel, while those signals that do not match the preset feature template are eliminated. These non-matching signals are likely to be false targets; this method can further improve the accuracy of target detection and reduce the impact of false targets.

[0013] Furthermore, obtaining the third detection target signal includes: determining the unit to be detected in the distance dimension according to the range Doppler spectrum and the second detection target signal, and obtaining a reference unit according to the unit to be detected; obtaining a detection threshold based on the reference unit and a preset false alarm rate, and comparing the signal power of the unit to be detected with the detection threshold; if the signal power is less than the detection threshold, eliminating the corresponding second detection target signal; otherwise, retaining the corresponding second detection target signal; wherein all retained second detection target signals are used as the third detection target signal.

[0014] In the above technical solution, the core of constant false alarm rate detection is to adaptively adjust the detection threshold according to the background noise situation to ensure that a constant false alarm rate can be maintained in different noise environments; the signal power of the unit to be detected is compared with the detection threshold, and signals with signal power less than the detection threshold are eliminated. These signals are likely to be noise or false targets. This method can further improve the accuracy of target detection and reduce the interference of false targets.

[0015] Furthermore, obtaining the final detection target signal includes: extracting the first correlation feature and the second correlation feature based on the eliminated second detection target signal and the previous frame target signal, respectively, and calculating the correlation matching degree of the first correlation feature and the second correlation feature; if the correlation matching degree is greater than a preset correlation matching threshold, retaining the corresponding second detection target signal; otherwise, eliminating the corresponding second detection target signal; wherein, the third detection target signal and all currently retained second detection target signals are used as the final detection target signal.

[0016] In the above technical solution, the correlation matching degree can reflect the similarity degree of the target between different frames; by comparing the correlation matching degree with the preset correlation matching threshold, those signals with high correlation matching degree can be retained, which are likely to represent real targets, while those signals with low correlation matching degree can be eliminated, which may be false targets or interference signals; this method can further improve the accuracy and continuity of target detection.

[0017] Furthermore, it also includes: performing filtering and tracking processing based on the final detection target signal to correct the final detection target signal based on the filtering and tracking processing result.

[0018] In the above technical solution, the filtering and tracking processing can smooth the final detected target signal, remove some random noise and errors, and predict and correct the target's position and speed according to the target's motion law; through filtering and tracking processing, the stability and accuracy of target detection can be improved, providing more reliable information for subsequent decision-making and control.

[0019] Furthermore, based on the same concept, the present application also provides a target detection system, including: a signal acquisition module, used to acquire the range Doppler spectrum of the detection radar, and perform initial target detection based on the range Doppler spectrum to obtain a first detection target signal; a primary elimination module, used to perform channel separation on the transmission channel of the detection radar based on the first detection target signal to complete primary false target elimination and obtain a second detection target signal; a secondary elimination module, used to perform constant false alarm rate detection based on the second detection target signal to complete secondary false target elimination and obtain a third detection target signal; and a target detection module, used to correlate and match the secondary false target elimination result with the previous frame target signal to obtain a final detection target signal based on the correlation matching result and the third detection target signal.

[0020] In the above technical solution, the problem of missed detection of weak targets can be effectively solved while eliminating false targets under the frequency modulated continuous wave waveform system.

[0021] Furthermore, based on the same concept, the present application also provides a storage medium, in which a computer program is stored, wherein the computer program is configured to execute the target detection method when running.

[0022] Furthermore, based on the same concept, the present application also provides an electronic device, which includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, code set or instruction set, and the at least one instruction, the at least one program, the code set or instruction set is loaded and executed by the processor to implement the target detection method.

[0023] Compared with the prior art, the present invention has the following advantages: This application can effectively suppress false targets while taking into account the detection of weak targets, effectively solving the impact of false targets on performance under the millimeter wave radar waveform system. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is a flow chart of the target detection method described in this application.

[0025] Figure 2 This is a schematic diagram of the distance changing with the number of frames without correlation matching as described in this application.

[0026] Figure 3 This is a schematic diagram of the change in distance with the number of frames after the association matching described in this application.

[0027] Figure 4 This is a framework diagram of the target detection system described in this application. DETAILED DESCRIPTION

[0028] The target detection method, system, storage medium and electronic device of the present application are further described in detail below with reference to specific embodiments and drawings.

[0029] See Figure 1 , the present application provides a target detection method, comprising the following steps S100-S400.

[0030] S100: Acquire a range Doppler spectrum of a detection radar, and perform initial target detection according to the range Doppler spectrum to obtain a first detected target signal.

[0031] S200: performing channel separation on the transmission channel of the detection radar based on the first detection target signal to complete a false target elimination and obtain a second detection target signal.

[0032] S300: Performing constant false alarm rate detection based on the second detection target signal to complete secondary false target rejection and obtain a third detection target signal.

[0033] S400: performing correlation matching on the secondary false target elimination result and the target signal of the previous frame, so as to obtain a final detection target signal based on the correlation matching result and the third detection target signal.

[0034] In some embodiments, a radar echo signal is subjected to a fast Fourier transform in the range dimension and the velocity dimension respectively to obtain a range Doppler spectrum; on the range Doppler spectrum, target detection is first performed with a lower preset threshold to ensure that weak targets are detected, and false targets are also detected at this time; since the target energy is greater than the preset threshold, the subscript colNo corresponding to the target's range dimension and the subscript rowNo corresponding to the Doppler dimension are recorded. Since the waveforms transmitted from different channels are phase modulated, channel separation is required at this time to obtain the correct channel arrangement order for subsequent angle detection; while channel separation can remove some false targets, some false targets will still be retained (such as false sidelobes and targets with overlapping strong target echoes, which are similar to real targets and cannot be eliminated by channel separation); in order to eliminate such false targets, the target signals retained after the false targets are eliminated are subjected to constant false alarm rate detection in the range dimension (CA-CFAR (Cell Averaging Constant False Alarm Rate) can be used or RANGE-CFAR (Range Constant False Alarm Rate) can be used). Rate, distance constant false alarm rate); however, constant false alarm rate detection may cause weak targets to be eliminated, so the targets eliminated twice are correlated and matched with the target signals of the previous frame (such as distance, speed, etc.). When the targets eliminated in the secondary false target elimination can match the target signals of the previous frame, the targets are retained; all the targets retained are finally used as the final detected target signals.

[0035] Next, the above steps S100-S400 are described in detail.

[0036] The step S100 of acquiring the range Doppler spectrum of the detection radar includes: acquiring an echo signal based on a plurality of linear frequency modulation signals emitted by the detection radar; and performing fast Fourier transform on the echo signal based on the range dimension and the velocity dimension to acquire the range Doppler spectrum.

[0037] In some embodiments, the target vehicle is equipped with a stepped-frequency continuous-wave radar. Each transmit channel performs frequency and phase modulation between transmitted signals. The radar transmits N linear frequency-modulated signals, each with an increasing center frequency, and each linear frequency-modulated signal collects M data points. However, when these signals encounter surrounding vehicles, pedestrians, or other obstacles, a portion of the signal is reflected back, forming an echo signal. For example, on a highway, a linear frequency-modulated signal emitted by the radar encounters a car 100 meters ahead. The signal reflected by the car is received by the radar, resulting in an echo signal containing target information.

[0038] After receiving the echo signal, a Fast Fourier Transform (FFT) is first performed on it in the distance dimension. Taking the highway example above, the FFT in the distance dimension converts the echo signal from the time domain to the frequency domain. The target's distance can be determined based on the peak position in the frequency domain. For example, the frequency corresponding to a peak in the frequency domain can be converted to a target distance of 100 meters from the radar. A FFT in the velocity dimension is then performed. Due to the Doppler effect, the target's speed will cause the frequency of the echo signal to shift. The FFT in the velocity dimension can be used to analyze this shift and thus determine the target's velocity. Assuming that the calculated speed of the car ahead is 20 meters per second relative to the vehicle, integrating the distance and velocity information yields the range-Doppler spectrum, which intuitively displays the target's distribution in both distance and velocity dimensions.

[0039] In the above technical solution, the linear frequency modulation signal is an important form of transmitting signal in the frequency-stepped frequency modulation radar. It has the advantage of being equivalent to a large bandwidth in the slow time dimension, which can improve the radar's range resolution; performing a fast Fourier transform in the distance dimension can convert the echo signal from the time domain to the frequency domain, thereby obtaining the target's distance information; performing a fast Fourier transform in the velocity dimension can obtain the target's velocity information. Through these two-step transformation, the range Doppler spectrum can be accurately constructed, intuitively displaying the target's distribution in the two dimensions of distance and velocity, and providing a clear data basis for subsequent target detection.

[0040] Furthermore, obtaining the first detected target signal in step S100 includes: performing initial target detection on the range Doppler spectrum with a preset threshold to obtain an echo signal with target energy greater than the preset threshold as the first detected target signal.

[0041] In some embodiments, a lower preset threshold is set to ensure that weak targets are detected. In this case, more targets will be detected, including weak targets and false targets. For example, if the preset threshold is set to 50, in the range Doppler spectrum, after scanning, it is found that the signal energy of several areas exceeds 50. The echo signals corresponding to these areas are considered to be possible target signals and serve as the first detected target signals.

[0042] In the above technical solution, echo signals with strong energy that may represent real targets can be quickly screened out, and some noise and interference signals with weaker energy can be preliminarily eliminated, thereby reducing the amount of data for subsequent processing and improving processing efficiency. At the same time, the preset threshold can be adjusted according to the actual application scenario, which has a certain degree of flexibility and is not limited to 50.

[0043] Furthermore, obtaining the second detection target signal in step S200 includes: performing feature analysis based on the first detection target signal to obtain signal features; performing feature matching on the signal features with a preset feature template to assign the first detection target signal with successful feature matching to the corresponding channel; wherein, if the signal features fail to match the features of the preset feature template, the corresponding first detection target signal is eliminated, and the first detection target signal in each channel is used as the second detection target signal.

[0044] In some embodiments, a feature analysis is performed on the first detection target signal just obtained; for example, the frequency change characteristics of the signal are analyzed. Taking a first detection target signal as an example, it is found that its frequency change has a certain fluctuation pattern within a period of time, and these frequency change characteristics are the characteristics of the signal.

[0045] The preset feature templates are pre-set based on feature ranges. For example, templates with multiple frequency ranges are preset. The signal features just analyzed are compared with the frequency ranges corresponding to these preset feature templates. If the frequency variation of a first detection target signal falls within the frequency variation range of a preset feature template, then this signal is assigned to the channel of that feature template. If a first detection target signal does not fall within the frequency variation range of any preset feature template, it is eliminated; the first detection target signal retained in each channel becomes the second detection target signal.

[0046] It should be noted that when performing feature analysis, the amplitude or phase of the signal can also be analyzed, and a feature template corresponding to the amplitude or phase can be set to achieve feature matching; technical personnel in this field can make their own choices based on the actual application scenario and are not limited to this.

[0047] In the above technical solution, the preset feature template is pre-set based on the known target features; through feature matching, the first detection target signal can be assigned to the corresponding channel, while those signals that do not match the preset feature template are eliminated. These non-matching signals are likely to be false targets; this method can further improve the accuracy of target detection and reduce the impact of false targets.

[0048] Furthermore, obtaining the third detection target signal in step S300 includes: determining the unit to be detected in the distance dimension according to the range Doppler spectrum and the second detection target signal, and obtaining a reference unit based on the unit to be detected; obtaining a detection threshold based on the reference unit and a preset false alarm rate, and comparing the signal power of the unit to be detected with the detection threshold; if the signal power is less than the detection threshold, eliminating the corresponding second detection target signal; otherwise, retaining the corresponding second detection target signal; wherein all retained second detection target signals are used as the third detection target signal.

[0049] In some embodiments, in the range Doppler spectrum, the unit to be detected in the range dimension is determined based on the position of the second detection target signal. For example, for a certain second detection target signal, an area within a certain range is selected as the unit to be detected with its position in the range dimension as the center. Then, some areas around the unit to be detected are selected as reference units. The reference units are used to estimate the power of background noise. Assuming that the unit to be detected is within a range of 90-110 meters from the radar, the reference units can be selected within a range of 80-90 meters and 110-120 meters from the radar.

[0050] The above detection thresholds can be obtained using CA-CFAR (Cell Averaging Constant False Alarm Rate) or RANGE-CFAR (Range Constant False Alarm Rate). Specifically: CA-CFAR: Calculates the average power of the signal within the reference cell as an estimate of the background noise power. Calculates the detection threshold based on the preset false alarm rate and the estimated background noise power.

[0051] RANGE-CFAR: Sorts the signal power within the reference cell to obtain an ordered signal sequence. A statistic (such as the median) in the sorted signal sequence is selected as the estimated value of the background noise power. Similar to CA-CFAR, the detection threshold is calculated based on the preset false alarm rate and the estimated value of the background noise power.

[0052] Assuming the calculated detection threshold is 60, the signal power of the second detection target signal in the unit to be detected is compared with the detection threshold; if the signal power of a second detection target signal is less than 60, it means that this signal is likely to be noise or a false target and is eliminated; if it is greater than or equal to 60, the signal is retained; finally, all retained second detection target signals become third detection target signals.

[0053] In the above technical solution, the core of constant false alarm rate detection is to adaptively adjust the detection threshold according to the background noise situation to ensure that a constant false alarm rate can be maintained in different noise environments; the signal power of the unit to be detected is compared with the detection threshold, and signals with signal power less than the detection threshold are eliminated. These signals are likely to be noise or false targets. This method can further improve the accuracy of target detection and reduce the interference of false targets.

[0054] It should be noted that due to the frequency modulation step frequency, the stationary target band is not a straight line, and there is a low noise rise around the target. After the constant false alarm rate detection, the real target will be eliminated, such as pedestrian and electric vehicle targets around iron railings and iron walls. Weak targets around strong targets will be mistakenly eliminated, so further association detection is performed based on the secondary eliminated targets.

[0055] Furthermore, obtaining the final detection target signal in step S400 includes: extracting the first correlation feature and the second correlation feature based on the eliminated second detection target signal and the previous frame target signal, respectively, and calculating the correlation matching degree of the first correlation feature and the second correlation feature; if the correlation matching degree is greater than a preset correlation matching threshold, retaining the corresponding second detection target signal; otherwise, eliminating the corresponding second detection target signal; wherein, the third detection target signal and all currently retained second detection target signals are used as the final detection target signal.

[0056] In some embodiments, for the second detected target signal that is removed from the current frame, its associated features, such as the target's position, speed, and direction of movement, are extracted as first associated features. Simultaneously, the same type of associated features are extracted from the target signal from the previous frame as second associated features. For example, a second detected target signal in the current frame corresponds to a target position of 100 meters from the radar, a speed of 20 meters per second, and a forward movement direction; while the corresponding target position in the previous frame is 98 meters from the radar, a speed of 21 meters per second, and also a forward movement direction. The similarity between these two sets of features is calculated to determine the associated matching degree.

[0057] A correlation matching threshold is preset, such as 0.8; if the calculated correlation matching degree is greater than 0.8, it means that the target has a high continuity between the two frames and is a real target, and the second detection target signal that was previously eliminated is retained; otherwise, the second detection target signal is truly eliminated; finally, the third detection target signal retained after the second elimination and the second detection target signal retained after correlation matching become the final detection target signal.

[0058] See Figure 2 and Figure 3, which are respectively a schematic diagram of the distance changing with the number of frames without associated matching, and a schematic diagram of the distance changing with the number of frames with associated matching; it can be found that the present application effectively proposes false targets while well retaining the detection of weak targets next to strong targets.

[0059] In the above technical solution, the correlation matching degree can reflect the similarity degree of the target between different frames; by comparing the correlation matching degree with the preset correlation matching threshold, those signals with high correlation matching degree can be retained, which are likely to represent real targets, while those signals with low correlation matching degree can be eliminated, which may be false targets or interference signals; this method can further improve the accuracy and continuity of target detection.

[0060] Furthermore, the step S400 further includes: performing filtering and tracking processing based on the final detected target signal, so as to correct the final detected target signal based on the filtering and tracking processing result.

[0061] In some embodiments, the final detected target signal is processed using a filtering method such as a Kalman filter. For example, using the target on the highway as an example, the target's position and velocity information is obtained based on the final detected target signal. Over time, this information may fluctuate due to factors such as measurement errors. Kalman filtering, combined with the target's motion model and previously measured values, predicts and corrects the target's position and velocity. For example, based on the Kalman filter results, the target's position is corrected from a previously measured 100 meters to 100.2 meters, and its velocity is corrected from 20 meters / second to 19.8 meters / second, thereby improving the accuracy and stability of target detection.

[0062] It should be noted that the filtering and tracking processing is optional in practical applications, and those skilled in the art will select it based on computing power and memory conditions.

[0063] In the above technical solution, the filtering and tracking processing can smooth the final detected target signal, remove some random noise and errors, and predict and correct the target's position and speed according to the target's motion law; through filtering and tracking processing, the stability and accuracy of target detection can be improved, providing more reliable information for subsequent decision-making and control.

[0064] In summary, the target detection method adopts a staged approach to remove false targets. By analyzing the signal characteristics of different transmission channels through channel separation, false targets caused by factors such as echo aliasing are found and removed. Secondly, false targets caused by target distance coupling are further removed through constant false alarm rate detection. Furthermore, through correlation matching, accidental interference signals are eliminated, the accuracy and continuity of the target are improved, and the problem of missed detection of weak targets is effectively solved. It can be seen that this application can achieve false target removal and weak target detection under limited storage space / computing power resources.

[0065] Further, based on the same concept, see Figure 4 The present application also provides a target detection system, including: a signal acquisition module, used to obtain the range Doppler spectrum of the detection radar, and perform initial target detection based on the range Doppler spectrum to obtain a first detection target signal; a primary elimination module, used to perform channel separation on the transmission channel of the detection radar based on the first detection target signal to complete primary false target elimination and obtain a second detection target signal; a secondary elimination module, used to perform constant false alarm rate detection based on the second detection target signal to complete secondary false target elimination and obtain a third detection target signal; and a target detection module, used to correlate and match the secondary false target elimination result with the target signal of the previous frame to obtain a final detection target signal based on the correlation matching result and the third detection target signal.

[0066] It should be noted that the target detection system and the above target detection method are based on the same inventive concept, and their specific implementation methods are not described in detail here.

[0067] In the above technical solution, the problem of missed detection of weak targets can be effectively solved while eliminating false targets under the frequency modulated continuous wave waveform system.

[0068] Furthermore, based on the same concept, the present application also provides a storage medium, in which a computer program is stored, wherein the computer program is configured to execute the target detection method when running.

[0069] In some embodiments, the storage medium stores several computer programs for causing a device to perform all or part of the steps of the methods described in various embodiments of the present application. The medium may include various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory, a random access memory, a magnetic disk, or an optical disk.

[0070] Furthermore, based on the same concept, the present application also provides an electronic device, which includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, code set or instruction set, and the at least one instruction, the at least one program, the code set or instruction set is loaded and executed by the processor to implement the target detection method.

[0071] In some embodiments, the memory and processor are interconnected via a bus; the processor may be one or more CPUs. If the processor is a single CPU, the CPU may be a single-core CPU or a multi-core CPU. The processor is used to control various functional modules of the electronic device and process signals. The memory includes, but is not limited to, RAM (Random Access Memory), ROM (Read-Only Memory), EPROM (Erasable Programmable Read-Only Memory), and CD-ROM (Compact Disc Read-Only Memory). The memory is used to store computer programs, operating systems, various applications, and data, such as a computer program for implementing the target detection method.

[0072] Although example embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above example embodiments are merely illustrative and are not intended to limit the scope of the present application. Various changes and modifications may be made therein by those skilled in the art without departing from the scope and spirit of the present application. All such changes and modifications are intended to be included within the scope of the present application as required by the appended claims.

[0073] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0074] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units described is merely a logical function division. In actual implementation, other division methods may be used, such as combining or integrating multiple units or components into another device, or ignoring or not performing some features.

[0075] The various component embodiments of the present application can be implemented in hardware, or in a software module running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all of the functions of some modules according to the embodiments of the present application. The application can also be implemented as a part or all of a device program (e.g., a computer program and a computer program product) for performing the method described herein. Such a program implementing the present application can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0076] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0077] Although the present application is described in conjunction with the above specific embodiments, it is obvious that those skilled in the art can make many substitutions, modifications and variations based on the above content. Therefore, all such substitutions, improvements and variations are included in the spirit and scope of the appended claims.

Claims

1. A target detection method, characterized in that: The following steps are involved: Acquiring a range Doppler spectrum of a detection radar, and performing initial target detection based on the range Doppler spectrum to obtain a first detected target signal; performing channel separation on a transmission channel of the detection radar based on the first detection target signal to eliminate false targets and obtain a second detection target signal; Performing constant false alarm rate detection based on the second detection target signal to complete secondary false target rejection and obtain a third detection target signal; And, the secondary false target elimination result is associated and matched with the target signal of the previous frame to obtain a final detection target signal based on the associated matching result and the third detection target signal.

2. The target detection method according to claim 1, wherein: The obtaining of the range Doppler spectrum of the detection radar includes: obtaining an echo signal based on a plurality of linear frequency modulation signals transmitted by the detection radar; Fast Fourier transform is performed on the echo signal based on the range dimension and the velocity dimension to obtain a range Doppler spectrum.

3. The target detection method according to claim 2, wherein: The obtaining of the first detection target signal includes: On the range Doppler spectrum, initial target detection is performed with a preset threshold value to obtain an echo signal with target energy greater than the preset threshold value as the first detected target signal.

4. The target detection method according to claim 3, wherein: The obtaining of the second detection target signal includes: Performing feature analysis based on the first detection target signal to obtain signal features; Performing feature matching on the signal feature and a preset feature template to assign the first detection target signal with successful feature matching to the corresponding channel; If the signal feature fails to match the preset feature template feature, the corresponding first detection target signal is discarded, and the first detection target signal in each channel is used as the second detection target signal.

5. The target detection method according to claim 4, characterized in that: The obtaining of the third detection target signal includes: Determine a unit to be detected in the range dimension according to the range Doppler spectrum and the second detection target signal, and obtain a reference unit according to the unit to be detected; Obtaining a detection threshold based on the reference unit and a preset false alarm rate, and comparing the signal power of the unit to be detected with the detection threshold, if the signal power is less than the detection threshold, eliminating the corresponding second detection target signal; otherwise, retaining the corresponding second detection target signal; Wherein, all the retained second detection target signals are used as third detection target signals.

6. The target detection method according to claim 5, characterized in that: The obtaining of the final detection target signal comprises: Extracting a first correlation feature and a second correlation feature based on the eliminated second detection target signal and the previous frame target signal, respectively, and calculating a correlation matching degree between the first correlation feature and the second correlation feature; if the correlation matching degree is greater than a preset correlation matching threshold, retaining the corresponding second detection target signal; otherwise, eliminating the corresponding second detection target signal; The third detection target signal and all currently retained second detection target signals are taken as the final detection target signal.

7. The target detection method according to claim 6, characterized in that: Also includes: A filter tracking process is performed based on the final detected target signal to correct the final detected target signal based on a filter tracking process result.

8. A system using the target detection method according to any one of claims 1 to 7, characterized in that: include: a signal acquisition module, configured to acquire a range Doppler spectrum of the detection radar and perform initial target detection based on the range Doppler spectrum to obtain a first detected target signal; a primary elimination module, configured to perform channel separation on the transmission channel of the detection radar based on the first detection target signal, so as to complete a false target elimination and obtain a second detection target signal; a secondary rejection module, configured to perform constant false alarm rate detection based on the second detection target signal to complete secondary false target rejection and obtain a third detection target signal; and a target detection module, configured to perform correlation matching on the secondary false target elimination result and the target signal of the previous frame, so as to obtain a final detection target signal based on the correlation matching result and the third detection target signal.

9. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to execute the target detection method according to any one of claims 1 to 7 when running.

10. An electronic device, characterized in that: The electronic device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the target detection method according to any one of claims 1 to 7.

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