A target detection false alarm identification method and system and a storage medium

Abstract

This application proposes a target detection false alarm identification method, system, and storage medium. The method includes: acquiring the maximum frequency value of each target distance dimension within a detection distance range in the judgment frequency range; comparing the maximum frequency value with a preset breathing frequency range to obtain live targets within the detection distance range; acquiring a final detected target value within the detection distance range based on the live target; and comparing the final detected target value with a preset distance detection value, wherein a target detection false alarm is determined when the final detected target value is less than the preset distance detection value. The method provided in this application effectively solves the problem of false alarms caused by interference from swaying objects or abnormal changes in radar signals caused by rain and noise when in-vehicle radar equipment detects live targets. It effectively reduces the false alarm probability and enhances the system's adaptability and robustness to the environment.

Description

Technical Field

[0001] This application belongs to the field of wireless communication technology, specifically relating to a target detection false alarm identification method, system, and storage medium. Background Technology

[0002] With cars becoming increasingly essential for transportation, news reports frequently feature stories of accidents caused by children being left unattended inside cars or school buses. This is especially true during the hot summer months when the temperature inside vehicles rises rapidly, significantly increasing the risk of injury or death to children accidentally left inside. With the development and civilian application of UWB (Ultra-Wideband) technology, which experienced explosive growth in 2022, UWB radar is now being used for in-vehicle life detection to reduce accidents caused by children being left in vehicles.

[0003] UWB radar transmits UWB pulse signals and receives the echoes after the pulse signals are reflected by obstacles. By analyzing the echo disturbances, it determines whether an object (or person) is nearby. A single pulse signal typically requires multiple samplings in the time domain. UWB radar liveness detection primarily relies on judging the breathing characteristics of a person in a stationary state or the amplitude of a person's movement in an active state to determine whether someone is inside the vehicle. For breathing characteristic detection, the commonly used algorithms on the market accumulate UWB radar data over a period of time, perform bandpass filtering, and then perform Fourier transform to obtain the time-frequency domain RD spectrum data. The frequency and the presence of a target are then determined based on the RD spectrum.

[0004] Minor vibrations from objects inside the vehicle, such as fan blades and hanging decorations, can generate radar reflections similar to human movement after bandpass filtering, causing the system to misinterpret them as target presence. The scattering of radar waves by raindrops during rainfall, as well as random noise from other non-target sources in the environment, can all cause abnormal changes in radar signals, increasing the false alarm rate. Summary of the Invention

[0005] To address the aforementioned technical problems, this application proposes a target detection false alarm identification method, system, and storage medium that can effectively reduce the false alarm rate.

[0006] Specifically, this application proposes a method for identifying false alarms in target detection, including:

[0007] Obtain the maximum frequency value of each target distance dimension within the detection distance range in the judgment frequency range.

[0008] The maximum frequency value is compared with a preset respiratory frequency range to obtain the live target within the detection distance range.

[0009] The final detection target value within the detection distance range is obtained based on the live target.

[0010] Furthermore, the final detected target value is compared with a preset distance detection value, and when the final detected target value is less than the preset distance detection value, a false alarm for target detection is determined.

[0011] In the above technical solution, by obtaining the maximum probability value of each distance dimension within the judgment frequency range in the detection distance range and comparing it with a preset breathing frequency range, live targets can be effectively identified, thus significantly improving the accuracy of target detection. By obtaining the final target value within the detection distance range based on the live target and comparing it with a preset distance detection value, a false alarm is determined when the final target value is less than the preset distance detection value. This method effectively reduces false alarms and avoids incorrect judgments caused by environmental noise or interference. Frequency analysis of each distance dimension allows the system to adapt to target detection needs in complex environments, improving the system's adaptability and reliability. Comparing the maximum frequency value with the preset breathing frequency range optimizes the target detection process, improving target detection efficiency and accuracy.

[0012] As one implementation method, obtaining the maximum frequency value of each target distance dimension within the detection distance range in the judgment frequency range includes:

[0013] Obtain the first energy sum of each distance dimension within the detection distance range and the second energy sum within the total detection frequency range; based on the first energy sum and the second energy sum, obtain the energy ratio of each distance dimension within the judgment frequency range; obtain the value of the energy ratio that is greater than a preset energy threshold; when the value is greater than the preset value threshold, obtain the maximum frequency value of each target distance dimension within the judgment frequency range; wherein, the target distance dimension is the distance dimension corresponding to the energy ratio being greater than the preset energy threshold.

[0014] By calculating the sum of the first energy in the judgment frequency range and the sum of the second energy in the total detection frequency range for each distance dimension within the detection range, and then calculating the energy ratio based on these two sums, the frequency ranges with concentrated energy can be effectively filtered out. This effectively avoids the influence of noise or interference that may exist in directly extracting frequency values, thus improving the accuracy of frequency value acquisition. Filtering the energy ratio by setting a preset energy threshold enhances the robustness of target detection and reduces the possibility of false positives. The calculation and filtering of energy ratios effectively identifies noise and interference, improving the system's adaptability. By calculating the maximum frequency value of the target distance dimension, the energy-concentrated distance range can be effectively focused, thereby reducing interference from invalid distance dimensions and improving the accuracy and efficiency of target detection.

[0015] Furthermore, the first energy sum and the second energy sum are obtained at least through the range frequency domain spectrum, which is obtained at least by performing a Fourier transform on the radar signal.

[0016] By converting radar signals from the time domain to the frequency domain using Fourier transform to generate a range-frequency spectrum, the signal energy of different range dimensions and frequency ranges can be clearly separated. This significantly improves the accuracy of energy calculation and avoids the negative impact of noise and interference in the time domain signal on energy calculation. This effectively improves the efficiency of energy calculation and the accuracy of target detection.

[0017] Furthermore, acquiring the live target within the detection distance range includes:

[0018] The maximum frequency value is compared with a preset breathing frequency range. If the maximum frequency value is within the preset breathing frequency range, it is determined that there is a live target in the current detection distance range; otherwise, it is determined that there is no live target in the current detection distance range.

[0019] By comparing the maximum frequency value with a preset respiratory frequency range, the respiratory characteristics of living targets can be effectively identified. This fully utilizes the physiological characteristics of living targets, significantly improving the accuracy of live target detection. Only when the maximum frequency value falls within the specified respiratory frequency range is a living target determined to exist within the current detection range, effectively filtering out non-living targets and thus significantly reducing the false positive rate. It effectively eliminates interference signals from non-living targets, enhancing the robustness of target detection. It avoids complex signal processing steps, improving the efficiency of target detection.

[0020] Furthermore, obtaining the final detected target value within the detection distance range based on the live target includes:

[0021] When a live target is present within the detection distance range, a variance array of the detection frequency within a preset time range for each target distance dimension is obtained; a preset variance threshold is compared with the variance array, and when the variance of a preset judgment value in the variance array is greater than the preset variance threshold, the detection target value is obtained.

[0022] By calculating the variance array of the detection frequency of each target distance within a preset time range and comparing it with a preset variance threshold, the detection of live targets can be effectively verified, improving the reliability of target detection and avoiding false positives caused by a single judgment mechanism. Further judgment using the preset variance threshold effectively enhances the robustness of target detection, enabling it to adapt to the target detection needs of various complex environments. A target value is only recorded when the variance of a preset judgment value in the variance array exceeds the preset variance threshold. This rigorous verification mechanism effectively filters out false positives caused by noise or interference, thereby reducing the false positive rate.

[0023] Furthermore, obtaining the final detected target value within the detection distance range further includes:

[0024] The variance array of the detection frequency for each target distance dimension within the detection range is iteratively detected until all variance arrays have been detected, in order to obtain the final detected target value.

[0025] By iteratively detecting the variance array of the detection frequency for each target distance dimension within the detection range, all target distance dimensions within the detection range can be comprehensively covered, ensuring comprehensive target detection, avoiding omissions, and enhancing the accuracy and reliability of target detection. By iteratively detecting the variance array of each target distance dimension, multiple targets can be effectively identified and distinguished, supporting multi-target detection and suitable for target detection needs in complex scenarios.

[0026] Furthermore, the determination of false positives in target detection includes:

[0027] The final detected target value is compared with the preset distance detection value. If the final detected target value is less than the preset distance detection value, it is determined that there is no live target in the detection distance range, and the target detection is determined to be a false alarm.

[0028] If the final detected target value is greater than or equal to the preset distance detection value, then it is determined that there is a live target within the detection distance range, and the target detection is accurate.

[0029] By comparing the final detected target value with a preset distance detection value, the system can effectively distinguish between real moving targets and false alarms, avoiding incorrect judgments caused by false alarms and effectively improving the accuracy of false alarm detection. Only when the final detected target value is greater than or equal to the preset distance detection value will a live target be determined to exist, thereby effectively reducing the false alarm rate of target detection.

[0030] Based on the same inventive concept, this application also proposes a system for identifying false alarms in target detection, the system comprising:

[0031] The frequency acquisition module is used to acquire the maximum frequency value of each target distance dimension in the judgment frequency range within the detection distance range.

[0032] The target detection module is used to compare the maximum frequency value with a preset respiratory frequency range to obtain live targets within the detection distance range.

[0033] The numerical statistics module is used to obtain the final detection target value within the detection distance range based on the live target.

[0034] In addition, a false alarm identification module is used to compare the final detected target value with a preset distance detection value, so as to determine a false alarm when the final detected target value is less than the preset distance detection value.

[0035] Furthermore, the numerical statistics module also includes a loop detection module, which is used to loop detection of the variance array of the detection frequency of each target distance dimension in the detection distance range, obtain the detection target value based on the variance array, until the variance array of the detection frequency of all target distance dimensions has been detected, and obtain the final detection target value.

[0036] Based on the same inventive concept, this application also proposes a computer-readable storage medium storing computer-executable instructions that can be read and executed by a control processor to perform the target detection false alarm identification method.

[0037] Compared with the prior art, this application has at least the following beneficial effects:

[0038] The method provided in this application effectively solves the problem of false alarms caused by interference from swaying objects or abnormal changes in radar signals due to rain or noise when in-vehicle radar equipment detects living targets. By obtaining the maximum probability value of each target distance dimension within the judgment frequency range in the detection range and comparing it with a preset breathing frequency range, living targets can be effectively identified, significantly improving the accuracy of target detection. By obtaining the final detected target value within the detection range based on the living target and comparing the final detected target value with a preset distance detection value, a false alarm is determined when the final target value is less than the preset distance detection value. This method effectively reduces the occurrence of false alarms and avoids incorrect judgments caused by environmental noise or interference. Through frequency analysis of each distance dimension, the system can adapt to the target detection requirements in complex environments, improving the system's adaptability and reliability. The comparison of the maximum frequency value with the preset breathing frequency range optimizes the target detection process, improving target detection efficiency and accuracy. Attached Figure Description

[0039] Figure 1 This is a flowchart illustrating a target detection false alarm identification method according to an embodiment of this application.

[0040] Figure 2 This is a schematic diagram of a target detection false alarm identification system shown in an embodiment of this application. Detailed Implementation

[0041] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0042] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0043] Example 1:

[0044] Please refer to Figure 1 The target detection false alarm identification method mainly includes steps S1 to S4.

[0045] Step S1 includes: obtaining the maximum frequency value of each target range dimension within the detection range in the judgment frequency range. The detection range can primarily be the detection range of all range dimensions in the range frequency spectrum obtained by performing conventional static filtering on the echo signal from the radar device, followed by Fourier transform. The radar device can primarily be a UWB (Ultra-Wideband) radar, but is not limited to this. The target range dimension is primarily the range dimension whose energy ratio of the first energy sum in the preset judgment frequency range to the second energy sum in the total detection frequency range is greater than a preset energy threshold.

[0046] Step S2 includes: comparing the maximum frequency value with a preset breathing frequency range to obtain a live target within the detection distance range. The preset breathing frequency range can primarily be from 0.1Hz to 2Hz. Those skilled in the art can adjust the preset breathing frequency range according to actual conditions, and are not limited to this. When the maximum frequency value is within the preset breathing frequency range, it is determined that a live target exists within the current detection distance range; when the maximum frequency value is not within the preset breathing frequency range, it is determined that no live target exists within the current detection distance range.

[0047] Step S3 includes: obtaining the final detected target value within the detection distance range based on the live target. This is primarily achieved by calculating the variance array of detection frequencies across all target distance dimensions within a preset time range when a live target is detected. The variance array is then compared to a preset variance threshold. A detected target value is obtained when the variance array contains a variance equal to a preset judgment value. The preset time range is typically 8 seconds. Detection is performed every 2 seconds, accumulating to 4 times, to obtain the variance array of detection frequencies within 8 seconds for each target distance dimension. The preset variance threshold is set based on the noise level and signal strength in the actual application scenario. Those skilled in the art can set the preset variance threshold according to the actual application scenario, for example, setting it to 0.4. The preset judgment value is typically 3, meaning a detected target value is recorded only when there are 3 variances in the variance array. The final detected target value is obtained by iteratively detecting the variance arrays of all target distance dimensions.

[0048] Step S4 includes comparing the final detected target value with a preset distance detection value, and determining a false alarm when the final detected target value is less than the preset distance detection value. The preset distance detection value is set primarily based on the detection distance range and detection accuracy requirements. For example, the preset distance detection value can be set to 2. Those skilled in the art can set the preset distance detection value according to actual conditions, based on the detection distance range and detection accuracy requirements. A false alarm is determined only when the final detected target value is less than the preset distance detection value. For example, when the final detected target value is 1 and the preset distance detection value is 2, i.e., the final target value is less than the preset distance detection value, a false alarm is determined.

[0049] In practical implementation, the above-mentioned technologies can mainly be applied inside vehicles to detect potential hazards caused by children or pets left behind. For example, one or more UWB radar devices can be installed inside the vehicle. After statically filtering the received UWB radar echo signals, a range-frequency domain spectrum is obtained by performing a Fourier transform on the statically filtered echo signals. Based on this range-frequency domain spectrum, a detection range, a total detection frequency range, and a judgment frequency range are set. By calculating the energy ratio of the sum of the energy in each distance dimension of the range-frequency spectrum within the judgment frequency range and the total detection frequency range, the target distance dimension and its maximum frequency value within the judgment frequency range are obtained based on the energy ratio. By comparing the maximum frequency value with a preset breathing frequency range, if the maximum frequency value is within the preset breathing frequency range, a live target is determined to exist within the detection range. If a live target is present, the variance array of the detection frequencies within a preset time range for all target distance dimensions is calculated. This variance array is then compared with a preset variance threshold. If the variance array contains the variance of a preset judgment value, the detected target value is obtained. The final detected target value is compared with the preset distance detection value. When the final detected target value is less than the preset distance detection value, the target detection is determined to be a false alarm.

[0050] In some embodiments, obtaining the maximum frequency value of each target distance dimension in the detection distance range within the judgment frequency range includes:

[0051] Obtain the first energy sum of each distance dimension within the detection distance range and the second energy sum within the total detection frequency range; based on the first energy sum and the second energy sum, obtain the energy ratio of each distance dimension within the judgment frequency range; obtain the value of the energy ratio that is greater than a preset energy threshold; when the value is greater than the preset value threshold, obtain the maximum frequency value of each target distance dimension within the judgment frequency range; wherein, the target distance dimension is the distance dimension corresponding to the energy ratio being greater than the preset energy threshold.

[0052] The detection range can be the range of distances obtained from the range-frequency domain spectrum after Fourier transform processing of the radar signal. For example, the detection range can be [r1, r2, r3, r4, ..., rn]. The judgment frequency range can be [f1, f2], and the total detection frequency range can be [F1, F2]. The first energy sum of each distance dimension within the judgment frequency range can be S. r1 (f1,f2), S r2 (f1,f2), ...,S rn (f1,f2), the sum of the second energy of each distance dimension within the total detection range can be mainly represented by SS. r1 (F1,F2), SS r2 (F1,F2), ...,SS rn (F1,F2), the energy ratio of each distance dimension within the judgment frequency range is obtained based on the first energy sum and the second energy sum. This can be primarily represented as rate1 = S r1 (f1,f2) / SS r1 (F1,F2), ...,raten=S rn (f1,f2) / SS rn (F1, F2). The preset energy threshold can be a data threshold set according to actual conditions. For example, the preset energy threshold can be RATE_SH = 0.5. The target distance dimensions obtained based on the preset energy threshold can be r_i1, r_i1, ..., r_irate_cnt. The preset numerical threshold can be 3. For example, when the value rate_cnt > NUM_TH = 3, the maximum frequency value max_fre of each distance dimension in the judgment frequency range is obtained. Those skilled in the art can set the preset numerical threshold according to actual conditions, and are not limited to it.

[0053] Optionally, the first energy sum and the second energy sum are obtained at least through the range frequency domain spectrum, which is obtained at least by performing a Fourier transform on the radar signal.

[0054] The radar signal can primarily be the echo signal obtained after the UWB radar transmits the signal and it is reflected by an obstacle or target. The range-frequency domain spectrum is obtained by performing a Fourier transform on the echo signal. Based on the detection range range in the range-frequency domain spectrum, the frequency range and the total detection frequency range are determined to obtain the first energy sum and the second energy sum.

[0055] Optionally, acquiring a live target within the detection distance range includes:

[0056] The maximum frequency value is compared with a preset breathing frequency range. If the maximum frequency value is within the preset breathing frequency range, it is determined that there is a live target in the current detection distance range; otherwise, it is determined that there is no live target in the current detection distance range.

[0057] For example, the preset breathing frequency range can be from 0.1Hz to 2Hz, primarily covering the breathing frequencies of humans and common pets. When the maximum frequency value `max_fre` is within the preset breathing frequency range, it is determined that a live target exists within the current detection range; otherwise, no live target exists within the current detection range. For example, when the maximum frequency value `max_fre` = 0.8Hz, since 0.1Hz < 0.8Hz < 2Hz, it is determined that a live target exists within the current detection range.

[0058] Optionally, obtaining the final detected target value within the detection distance range based on the live target includes:

[0059] When a live target is present within the detection distance range, obtain the variance array of the detection frequency within a preset time range for each target distance dimension.

[0060] The variance array is compared with a preset variance threshold, and the target value is obtained when the variance of a preset judgment value in the variance array is greater than the preset variance threshold.

[0061] The preset time range can be 8 seconds, with a sampling interval of 2 seconds. For example, when a live target is detected within the range, the variance arrays of each target distance dimension r_i1, r_i2, ..., r_irate_cnt within 8 seconds are obtained as vas(i,1), vas(i,2), vas(i,3), and vas(i,4). The preset variance threshold can be set by those skilled in the art according to the actual situation; for example, the preset variance threshold can be set to VAR_SH = 0.4. The preset judgment value can be 3, meaning that when at least 3 variances in the variance array are greater than the preset variance threshold, the target detection value detect_cnt = 1 is obtained.

[0062] Optionally, obtaining the final detected target value within the detection distance range further includes:

[0063] The variance array of the detection frequency for each target distance dimension within the detection range is iteratively detected until all variance arrays have been detected, in order to obtain the final detected target value.

[0064] By iteratively detecting the variance array of the detection frequency for each target distance dimension, when the variance of the variance array that is full of a preset value is greater than a preset variance threshold, the detected target value detect_cnt = detect + 1 is obtained, until the variance arrays of all target distance dimensions have been detected, and then the final detected target value is obtained.

[0065] Optionally, the determination of false positives in target detection includes:

[0066] The final detected target value is compared with the preset distance detection value. If the final detected target value is less than the preset distance detection value, it is determined that there is no live target in the detection distance range, and the target detection is determined to be a false alarm.

[0067] If the final detected target value is greater than or equal to the preset distance detection value, then it is determined that there is a live target within the detection distance range, and the target detection is accurate.

[0068] Those skilled in the art can set the preset distance detection value according to actual conditions. For example, the preset distance detection value can be set to RANGE_DETECT_MIN_CNT = 2. If the final detected target value is detect_cnt = 3, that is, the final detected target value is greater than the preset distance detection value, it is determined that there is a live target in the detection range, and the live target detection is accurate. If the final detected target value is detect_cnt = 1, that is, the final detected target value is less than the preset distance detection value, it is determined that there is no live target in the detection range, and the live target detection is a false alarm.

[0069] Example 2:

[0070] Please refer to Figure 2 This application also proposes a system using the target detection false alarm identification method described in Embodiment 1. The system mainly includes: a frequency acquisition module, a target detection module, a numerical statistics module, and a false alarm identification module.

[0071] The frequency acquisition module is used to acquire the maximum frequency value of each target range dimension within the detection range in the judgment frequency range. The detection range can primarily be the detection range within the range-frequency domain spectrum obtained after Fourier transform processing of the radar signal. The maximum frequency value of each target range dimension within the judgment frequency range is acquired based on the energy ratio calculated between the energy ratio of each range dimension within the detection range and the energy ratio within the total detection frequency range.

[0072] The target detection module compares the maximum frequency value with a preset breathing frequency range to identify live targets within the detection range. The preset breathing frequency range can be a pre-set range covering the breathing frequencies of humans and common pets, such as 0.1Hz to 2Hz. A live target is determined to exist within the current detection range only if the maximum frequency value falls within the preset breathing frequency range.

[0073] The numerical statistics module is used to obtain the final detected target value within the detection distance range based on the live target. When a live target is present, the variance array of each target distance dimension within a preset time range is detected cyclically. If the variance of a preset judgment value in the variance array is greater than a preset variance threshold, a detected target value is recorded once. This process continues until the variance arrays of all target distance dimensions have been detected, and the final detected target value is obtained.

[0074] The system also includes a false alarm detection module, used to compare the final detected target value with a preset distance detection value, and to determine a false alarm when the final detected target value is less than the preset distance detection value. For example, the preset distance detection value can be set to 2. When the final detected target value is greater than or equal to 2, it is determined that there is no false alarm; when the final detected target value is less than the preset distance detection value, it is determined that there is a false alarm.

[0075] Optionally, the numerical statistics module further includes a loop detection module, which is used to loop detect the variance array of the detection frequency of each target distance dimension in the detection distance range, obtain the detection target value based on the variance array, until the variance array of the detection frequency of all target distance dimensions has been detected, and obtain the final detection target value.

[0076] When the variance array of the detection frequency for any target distance dimension within the detection range contains a preset judgment value whose variance exceeds a preset variance threshold, a target value is recorded as detected. Through iterative detection, all target distance dimensions can be covered, avoiding inaccurate target values ​​due to missed detections and improving the accuracy of false alarm identification in target detection.

[0077] Example 3:

[0078] This application also proposes a computer-readable storage medium, the computer-readable storage medium comprising:

[0079] The computer-readable storage medium stores computer-executable instructions.

[0080] When the computer-executable instructions are executed by the control processor, the target detection false alarm identification method described in Embodiment 1 is implemented.

[0081] The computer-readable storage medium can be implemented entirely or partially by software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented entirely or partially as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in the computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0082] In summary, the method provided in this application effectively solves the problem of false alarms caused by interference from swaying objects or abnormal changes in radar signals due to rain or noise when in-vehicle radar equipment detects living targets. By obtaining the maximum probability value of each target distance dimension within the judgment frequency range in the detection range and comparing it with a preset breathing frequency range, living targets can be effectively identified, significantly improving the accuracy of target detection. By obtaining the final detected target value within the detection range based on the living target and comparing it with a preset distance detection value, a false alarm is determined when the final target value is less than the preset distance detection value. This method effectively reduces the occurrence of false alarms and avoids incorrect judgments caused by environmental noise or interference. Through frequency analysis of each distance dimension, the system can adapt to the target detection requirements in complex environments, improving the system's adaptability and reliability. The comparison of the maximum frequency value with the preset breathing frequency range optimizes the target detection process, improving target detection efficiency and accuracy.

[0083] In the several embodiments provided in this application, it will be understood that each block in the flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the figures. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved.

[0084] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause an electronic device to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0085] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of this application. It should be understood that the above descriptions are merely specific embodiments of this application and are not intended to limit the scope of protection of this application. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application for those skilled in the art.

Claims

1. A method for identifying false alarms in target detection, characterized in that, include: Obtain the maximum frequency value of each target distance dimension within the detection distance range in the judgment frequency range; The maximum frequency value is compared with a preset respiratory frequency range to obtain the living target within the detection distance range; Based on the live target, obtain the final detected target value within the detection distance range; Furthermore, the final detected target value is compared with a preset distance detection value, and when the final detected target value is less than the preset distance detection value, a false alarm for target detection is determined. The step of obtaining the maximum frequency value of each target distance dimension within the judgment frequency range in the detection distance range includes: Obtain the first energy sum of each distance dimension in the detection distance range within the judgment frequency range and the second energy sum within the total detection frequency range; Based on the first energy sum and the second energy sum, obtain the energy ratio of each distance dimension within the judgment frequency range; Obtain the value of the energy ratio that is greater than the preset energy threshold. When the value is greater than the preset value threshold, obtain the maximum frequency value of each target distance dimension within the judgment frequency range. Wherein, the target distance dimension is the distance dimension corresponding to the energy ratio being greater than a preset energy threshold.

2. The target detection false alarm identification method according to claim 1, characterized in that, The first energy sum and the second energy sum are obtained at least through the range frequency domain spectrum, which is obtained at least through Fourier transform of the radar signal.

3. The target detection false alarm identification method according to claim 1, characterized in that, The acquisition of live targets within the detection distance range includes: The maximum frequency value is compared with a preset breathing frequency range. If the maximum frequency value is within the preset breathing frequency range, it is determined that there is a live target in the current detection distance range; otherwise, it is determined that there is no live target in the current detection distance range.

4. The target detection false alarm identification method according to claim 1, characterized in that, The step of obtaining the final detected target value within the detection distance range based on the live target includes: When a live target is present within the detection distance range, obtain the variance array of the detection frequency within a preset time range for each target distance dimension; The variance array is compared with a preset variance threshold, and the target value is obtained when the variance of a preset judgment value in the variance array is greater than the preset variance threshold.

5. The target detection false alarm identification method according to claim 4, characterized in that, The step of obtaining the final detected target value within the detection distance range further includes: The variance array of the detection frequency for each target distance dimension within the detection range is iteratively detected until all variance arrays have been detected, in order to obtain the final detected target value.

6. The target detection false alarm identification method according to claim 1, characterized in that, The determination of false positives in target detection includes: The final detected target value is compared with the preset distance detection value. If the final detected target value is less than the preset distance detection value, it is determined that there is no live target in the detection distance range, and the target detection is determined to be a false alarm. If the final detected target value is greater than or equal to the preset distance detection value, then it is determined that there is a live target within the detection distance range, and the target detection is accurate.

7. A system based on the target detection false alarm identification method according to any one of claims 1-6, characterized in that, The system includes: The frequency acquisition module is used to acquire the maximum frequency value of each target distance dimension in the detection distance range within the judgment frequency range; The target detection module is used to compare the maximum frequency value with a preset respiratory frequency range to obtain live targets within the detection distance range; The numerical statistics module is used to obtain the final detection target value within the detection distance range based on the live target; In addition, a false alarm identification module is used to compare the final detected target value with a preset distance detection value, so as to determine a false alarm when the final detected target value is less than the preset distance detection value.

8. The system for identifying false alarms in target detection according to claim 7, characterized in that, The numerical statistics module also includes a loop detection module, which is used to loop detection of the variance array of the detection frequency of each target distance dimension in the detection distance range, obtain the detection target value based on the variance array, until the variance array of the detection frequency of all target distance dimensions has been detected, and obtain the final detection target value.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions that can be read and executed by a control processor as described in any one of claims 1-6.

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