CN117250609A - Method for smoothing in-cabin living body detection result, storage medium and electronic equipment - Google Patents
Method for smoothing in-cabin living body detection result, storage medium and electronic equipment Download PDFInfo
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- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
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Abstract
The invention provides a cabin living body detection result smoothing method, a storage medium and electronic equipment, and belongs to the technical field of radar signal processing. The living body detection result output adopts a gradual belief strategy, a detection zone bit is output every frame, the detection zone bit has two states of living body existence and non-existence, a certain number of detection zone marks are used as units for carrying out buffer memory area stacking, a method for calculating the confidence of the detection zone buffer memory area is adopted for result smoothing, namely a confidence threshold is set, the confidence of the buffer memory area is calculated after each detection zone stacking, the confidence obtained by calculation is compared with the confidence threshold to determine the living body detection output result, and different procedure scheduling is completed according to the state change of the cabin door. The invention can carry out confidence analysis on the in-cabin living body detection result, further smooth the living body detection result, overcome the defects of missing report and false report existing in the existing in-cabin living body detection technology based on millimeter wave radar, and greatly improve the accuracy of in-cabin living body detection.
Description
Technical Field
The invention belongs to the field of radar signal processing, and particularly relates to a method for smoothing in-cabin living body detection results, a storage medium and electronic equipment.
Background
In recent years, due to the increase of the number of automobiles, new automobile evaluation regulations in various countries in the world have been or are seeking to add in-car living body detection items to the new regulations, and the current living body detection technology is a car camera scheme, but the privacy protection of the living body detection technology is poor. Aiming at the problem, based on the advantages of good privacy protection, sensitive micro Doppler characteristics, low cost and the like of the millimeter wave radar, the FMCW millimeter wave radar becomes the mainstream choice for in-cabin living body detection. The human body respiration can modulate the radar echo, and the respiration information of the human body can be extracted by demodulating the echo signal, so that the respiration information is used as the basis of living body detection. However, the electromagnetic environment in the cabin is complex, clutter and other interferences exist outside the living body, the living body cannot keep absolute rest, some tiny displacements of the living body and other interferences which do not affect the Doppler motion feature extraction but affect the respiratory feature extraction can cause the living body detection result to be wrong in a short period of time, and the living body detection result also cannot change because the living body state in the cabin is unchanged only along with the cabin door state, namely, tiny missing report and false report generated by the interference can be eliminated through a proper technology, and how to effectively eliminate short-time missing report and false report and reduce missing report rate and false alarm rate in the living body detection process becomes important research content.
Disclosure of Invention
Aiming at the problems of false alarm and missing report during in-cabin motion living detection of a millimeter wave radar caused by strong clutter interference of moving targets such as a metal ornament which shakes greatly in a cabin in the prior art, the invention provides a smoothing method for in-cabin living detection results, a storage medium and electronic equipment, wherein the operation amount of the implementation method is small, and the implementation method is convenient for hardware implementation.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
the method for smoothing the in-cabin living body detection result is characterized by comprising the following steps of:
step 1: setting a result smooth buffer area for storing a living body detection mark obtained by each frame of a living body detection process;
step 2: setting the parameters of the result smooth cache region to zero, and emptying the result smooth cache region;
step 3: stacking the living body detection marks obtained by each frame of living body detection process;
step 4: after stacking a certain number of living body detection marks, calculating the confidence coefficient of the result smooth cache area;
step 5: setting a confidence coefficient threshold value, judging the relation between the confidence coefficient of the result smooth cache region and the threshold value, if the confidence coefficient of the result smooth cache region is larger than the threshold value, outputting a confidence result as an in-cabin living body detection result, otherwise, repeating the step 3 and the step 4;
step 6: and (3) continuously detecting the cabin door state mark, and restarting the flow from the step (2) if the cabin door state is changed.
In order to optimize the technical scheme, the specific measures adopted further comprise:
further, in step 1, the result is set to smooth the buffer area, and the stacking times M and the confidence CL of the buffer area after the Mth stacking are set M 。
Further, in step 2, the parameter setting of the result smoothing buffer area is specifically: the number of stacks m=0 is set, and the confidence cl=0 of the result smoothing buffer is set.
Further, in step 3, a boolean value of the biopsy flag is obtained for each frame in the biopsy procedure, which is specifically as follows:
the living body detection marks obtained by each frame of the living body detection process are stacked in units of N frames and stored in the result smoothing buffer, and the stacking times M=M+1 are counted for every N frames stacked.
Further, in step 4, the confidence calculation of the result smoothing buffer area is specifically as follows:
after M times of stacking, the result smooth buffer area shares M multiplied by N living body detection marks, and the confidence CL in the result smooth buffer area after M times of stacking is calculated M ：
Wherein K is true And K false The number of living body detection marks in the result smooth buffer area is True and False respectively.
Further, in step 5, a confidence Threshold is set, and the confidence CL obtained in step 4 is set M Comparing with Threshold, determining the subsequent steps of the smoothing flow according to the comparison result:
if CL M If more than Threshold, the living body state in the cabin is considered to be determined, the follow-up output result is always a confidence result, and the confidence result is a living body detection mark occupying a larger result smooth buffer area, specifically as follows:
if CL M If the Threshold is less than or equal to Threshold, considering that the living body state in the cabin is still undetermined, and repeating the steps 3 and 4 until CL M More than Threshold, the result is output as each frameThe results were not confidence.
Further, in step 6, door status flag detection occurs at CL M If the state of the cabin door is detected to be changed when the Threshold is less than or equal to Threshold, restarting the flow from the step 2; otherwise, repeating the step 3 and the step 4 until CL M ＞Threshold。
Further, in step 6, door status flag detection occurs at CL M If the cabin door state is detected to be changed when the Threshold is more than Threshold, the flow is restarted from the step 2 until CL M > Threshold; otherwise, continuing to output the confidence result.
In another aspect, the present invention also proposes a computer-readable storage medium storing a computer program, characterized in that the computer program causes a computer to execute the intra-cabin living detection result smoothing method as described above.
In another aspect, the present invention further provides an electronic device, including: the processor is used for realizing the in-cabin living body detection result smoothing method when executing the computer program.
The beneficial effects of the invention are as follows: the invention is based on radar signal processing step, the living body detection result output adopts a 'gradual belief' strategy, each frame outputs detection zone bit, the detection zone bit has two states of living body existence and non-existence, a certain number of detection zone bits are used as units to stack a buffer area, the result smoothing adopts a method for calculating the confidence coefficient of the buffer area of the detection zone, namely a confidence coefficient threshold value is set, the confidence coefficient calculation of the buffer area is carried out after each detection zone is stacked, the calculated confidence coefficient is compared with the confidence coefficient threshold value to determine the living body detection output result, and different flow scheduling is completed according to the state change of a cabin door.
The 'gradual belief' result smoothing strategy adopted by the invention effectively avoids the problem that the living body detection result is missed in a short period of time caused by small displacement of living body and other interference which does not influence Doppler motion characteristic extraction but influences respiratory characteristic extraction, and can realize that the detection missing report rate is 0 after the result belief; the method for setting the confidence threshold effectively avoids the problem that the detection result is misreported due to some tiny interference when no living body exists in the cabin, and can achieve the detection misreport rate of 0 after the result confidence; the cabin door state mark detection is continuously carried out in the smoothing process, so that errors caused by cabin door state change are effectively avoided, and the accuracy of in-cabin living body detection is further improved.
Drawings
Fig. 1 is a flowchart of a method for smoothing in-cabin living body detection results.
Fig. 2 is a schematic diagram of an intra-capsule biopsy marker stack and confidence calculation method.
Fig. 3 is a schematic diagram of a typical scene biopsy smoothing result.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings of the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
The method is characterized in that based on radar signal processing steps, a 'gradual belief' strategy is adopted for living body detection result output, detection zone bits are output every frame, the detection zone bits have two states of living body existence and non-existence, buffer memory area stacking is carried out by taking a certain number of detection zones as units, a method for calculating the confidence of the buffer memory area of the detection zone is adopted for result smoothing, namely a confidence threshold is set, the confidence calculation of the buffer memory area is carried out after each detection zone stacking, the confidence obtained by calculation is compared with the confidence threshold to determine living body detection output results, and different flow scheduling is completed according to cabin door state change.
In an embodiment, as shown in fig. 1, the present invention provides a method for smoothing in-cabin living body detection results, which is divided into four steps of pre-parameter setting, detection flag bit stacking, confidence calculation analysis and cabin door state flow scheduling.
Step one, setting front parameters.
Firstly, setting a result smooth buffer area for storing a living body detection mark of each frame, setting the stacking times M of the buffer area and the confidence CL of the buffer area after the Mth stacking M Setting both parameters to 0, namely M=0 and CL=0, and emptying the result smoothing buffer area, and setting a subsequent confidence judgment Threshold value Threshold.
And step two, detecting the flag bit stack.
Fig. 2 is a schematic diagram of a method for stacking in-cabin living body detection marks and calculating confidence coefficient, wherein a detection mark is obtained by each frame of a radar living body detection process, and the detection mark is a boolean value as follows:
the living body detection marks obtained by the living body detection process of each frame are stacked in units of N frames and stored in the buffer, and the stacking times M=M+1 of each stacked N frames.
And thirdly, calculating and analyzing the confidence coefficient.
The M times of stacking result smooth buffer areas share m×n living body detection marks, and the confidence of the result in the M times of stacking result buffer areas is calculated:
wherein K is true And K false The number of flags in the buffer at this time are True and False, respectively.
The confidence CL obtained above is used for M Comparing with confidence Threshold, determining the subsequent steps of the smoothing flow according to the comparison result, if CL M If more than Threshold, the living body state in the cabin is considered to be determined, the subsequent output result is always a confidence result, specifically, a detection mark with larger occupation in a result smoothing buffer area, namely
If CL M If the Threshold is less than or equal to Threshold, considering that the living body state in the cabin is still undetermined, repeating the steps of stacking the detection marks and calculating the confidence coefficient until CL M More than Threshold (M in the measured data does not exceed 8), the output result in the process is an untrusted result of each frame.
And step four, cabin door state flow scheduling.
One precondition for in-cabin living body detection is that the in-cabin living body state only changes along with the opening and closing of the cabin door, so that the cabin door state is continuously monitored in the result smoothing process, if the cabin door state changes, the stacking times, the confidence and the buffer areas obtained before are all emptied, and then the detection sign stacking and the confidence calculating steps are continued.
Cabin door status flag detection can be divided into two types according to a time line, specifically:
(1) Cabin door status flag detection occurs at CL M When the Threshold is less than or equal to Threshold, namely in the process of carrying out detection mark stacking calculation confidence, if the state change of the cabin door is detected, setting the stacking times M to 0, and clearing a buffer area, and subsequently, continuing to carry out detection mark stacking and confidence calculation steps; otherwise, directly performing detection mark stacking and confidence calculating steps until CL M ＞Threshold。
(2) Cabin door status flag detection occurs at CL M When the number of times is more than Threshold, namely after the living body state in the cabin is determined, if the cabin door state is detected to be changed, the stacking times M is set to 0, a buffer area is emptied, and the steps of stacking detection marks and calculating the confidence coefficient are carried out until CL M > Threshold; otherwise, continuing to output the result after confidence.
And the four steps finish the in-cabin living body detection result smoothing flow.
Fig. 3 is a schematic diagram of a typical scene living body detection smoothness result in an experiment, wherein the experimental scene is in a car cabin, a radar is installed at the top of a rear row, and radar configuration parameters are as follows: the initial frequency is 60GHz, the bandwidth is 4GHz, the ADC sampling rate is 20Msps, and the frequency modulation period and the frame period are 25.6us and 200ms respectively. The living body item simulates a real living body target by a simulation doll, is placed at a position of about 1m from the radar on the left foot pad, and is placed with an umbrella above the simulation doll, and the test duration is 650s. The method of the invention is adopted to smooth the living body detection result, the living body detection result before smoothing is the upper graph of fig. 3, the living body detection result after smoothing is the lower graph of fig. 3, and the missing report of the detection result which is not smooth in the experimental time period can be seen, and the missing report rate of the living body detection result after adopting the method of the invention is 0, which shows that the method of the invention has obvious improvement on the accuracy of in-cabin living body detection.
In another embodiment, the present invention proposes a computer-readable storage medium storing a computer program that causes a computer to execute the intra-cabin living detection result smoothing method as described in the first embodiment.
In another embodiment, the present invention provides an electronic device, including: the processor executes the computer program to implement the intra-cabin living body detection result smoothing method according to the first embodiment.
In the embodiments disclosed herein, a computer storage medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The computer storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a computer storage medium would include one or more wire-based electrical connections, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above examples, and all technical solutions belonging to the concept of the present invention belong to the protection scope of the present invention. It should be noted that modifications and adaptations to the invention without departing from the principles thereof are intended to be within the scope of the invention as set forth in the following claims.
Claims (10)
1. The method for smoothing the in-cabin living body detection result is characterized by comprising the following steps of:
step 1: setting a result smooth buffer area for storing a living body detection mark obtained by each frame of a living body detection process;
step 2: setting the parameters of the result smooth cache region to zero, and emptying the result smooth cache region;
step 3: stacking the living body detection marks obtained by each frame of living body detection process;
step 4: after stacking a certain number of living body detection marks, calculating the confidence coefficient of the result smooth cache area;
step 5: setting a confidence coefficient threshold value, judging the relation between the confidence coefficient of the result smooth cache region and the threshold value, if the confidence coefficient of the result smooth cache region is larger than the threshold value, outputting a confidence result as an in-cabin living body detection result, otherwise, repeating the step 3 and the step 4;
step 6: and (3) continuously detecting the cabin door state mark, and restarting the flow from the step (2) if the cabin door state is changed.
2. The intrabay biopsy result smoothing method of claim 1, wherein: in step 1, the result smoothing buffer is set, and the stacking times M and the post-stacking buffer of the Mth time are setZone confidence CL M 。
3. The intrabay biopsy result smoothing method of claim 1, wherein: in step 2, the parameter setting of the result smoothing buffer area is specifically: the number of stacks m=0 is set, and the confidence cl=0 of the result smoothing buffer is set.
4. The intrabay biopsy result smoothing method of claim 1, wherein: in step 3, a boolean value of the biopsy mark is obtained for each frame in the biopsy procedure, specifically as follows:
the living body detection marks obtained by each frame of the living body detection process are stacked in units of N frames and stored in the result smoothing buffer, and the stacking times M=M+1 are counted for every N frames stacked.
5. The intrabay biopsy result smoothing method of claim 4, wherein: in step 4, the confidence coefficient of the result smoothing buffer area is calculated as follows:
after M times of stacking, the result smooth buffer area shares M multiplied by N living body detection marks, and the confidence CL in the result smooth buffer area after M times of stacking is calculated M ：
Wherein K is true And K false The number of living body detection marks in the result smooth buffer area is True and False respectively.
6. The intrabay biopsy result smoothing method of claim 5, wherein: in step 5, a confidence is setThreshold, and confidence CL obtained in step 4 M Comparing with Threshold, determining the subsequent steps of the smoothing flow according to the comparison result:
if CL M If more than Threshold, the living body state in the cabin is considered to be determined, the follow-up output result is always a confidence result, and the confidence result is a living body detection mark occupying a larger result smooth buffer area, specifically as follows:
if CL M If the Threshold is less than or equal to Threshold, considering that the living body state in the cabin is still undetermined, and repeating the steps 3 and 4 until CL M The output results in the process are the untrusted results per frame, > Threshold.
7. The intrabay biopsy result smoothing method of claim 6, wherein: in step 6, door status flag detection occurs at CL M If the state of the cabin door is detected to be changed when the Threshold is less than or equal to Threshold, restarting the flow from the step 2; otherwise, repeating the step 3 and the step 4 until CL M ＞Threshold。
8. The intrabay biopsy result smoothing method of claim 6, wherein: in step 6, door status flag detection occurs at CL M If the cabin door state is detected to be changed when the Threshold is more than Threshold, the flow is restarted from the step 2 until CL M > Threshold; otherwise, continuing to output the confidence result.
9. A computer-readable storage medium storing a computer program, wherein the computer program causes a computer to execute the intra-capsule living body detection result smoothing method according to any one of claims 1 to 8.
10. An electronic device, comprising: memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the intra-capsule living detection result smoothing method according to any one of claims 1-8 when the computer program is executed.
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- 2023-08-22 CN CN202311063340.4A patent/CN117250609A/en active Pending
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