A method and system for identifying life detection signals based on MIMO digital array

Abstract

The present invention discloses a life detection signal recognition method and system based on a MIMO digital array, which relates to the field of life detection technology, including: forming a life detection signal feature library; multiple radar antennas based on the MIMO digital array transmit electromagnetic waves and receive reflected target echo signals; judging whether there is a living life signal based on the target echo signals of multiple radar antennas; if there is a living life signal, analyzing the physiological state of the living life; based on the physiological state of all living lives detected by the MIMO digital array, assessing the rescue priority urgency of each living life; based on the rescue priority urgency of all living lives, determining and generating a rescue coordination plan for all living lives. The advantages of the present invention are: effectively realizing high-precision detection of human targets in a static state, and providing a more efficient and accurate non-contact life detection solution for disaster relief, medical monitoring and other fields.

Description

Technical Field

[0001] The present invention relates to the technical field of life detection, and in particular to a life detection signal recognition method and system based on a MIMO digital array. Background Art

[0002] In the fields of disaster relief, medical monitoring, counter-terrorism investigation, etc., it is crucial to detect and identify life forms quickly and accurately. Traditional life detection technologies such as infrared detection and optical detection have limitations such as weak penetration and susceptibility to interference. MIMO (Multiple-Input Multiple-Output) digital array radar technology, with its powerful penetration ability, high resolution and anti-interference, provides a new solution for life detection. This project aims to develop a life detection signal recognition method and system based on MIMO digital array to achieve accurate positioning and vital sign monitoring of trapped people in complex environments such as under ruins and inside buildings. Summary of the invention

[0003] In order to solve the above technical problems, a life detection signal recognition method and system based on MIMO digital array is provided. This technical solution solves the limitations of the above-mentioned traditional life detection technologies such as infrared detection and optical detection, such as weak penetration and susceptibility to interference.

[0004] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0005] A life detection signal recognition method based on a MIMO digital array, comprising:

[0006] Establish a life detection signal feature library;

[0007] Multiple radar antennas based on the MIMO digital array transmit electromagnetic waves and receive the reflected echo signals, which are recorded as target echo signals;

[0008] Determine whether there is a Doppler frequency shift based on the target echo signals of multiple radar antennas, and if so, determine that there is a living life signal, and if not, determine that there is no living life signal;

[0009] If there is a living body’s life signal, the physiological state of the living body is analyzed based on the Doppler frequency shift characteristics of the target echo signals from multiple radar antennas;

[0010] Based on the physiological status of all living beings detected by the MIMO digital array and historical rescue experience, the rescue priority urgency of each living being is assessed;

[0011] Based on the rescue priority and urgency of all living lives, a coordinated rescue plan for all living lives is determined and generated.

[0012] Preferably, the building of a life detection signal feature library specifically includes:

[0013] Based on historical rescue experience, the actual postures of all rescued persons in actual rescues are collected and recorded as sample postures;

[0014] The Doppler frequency shift characteristics of the echo signals of the sample volunteers in different sample postures are collected by using a MIMO digital array, and recorded as sample Doppler frequency shift characteristics;

[0015] The sample Doppler frequency shift characteristics of multiple sample volunteers with different physiological characteristics at different distances are collected, and a one-to-one correspondence is established between all sample Doppler frequency shift characteristics and distance, sample body shape and physiological characteristics of sample volunteers to form a life detection signal feature library.

[0016] Preferably, the analysis of the physiological state of a living being based on the Doppler frequency shift characteristics of target echo signals from multiple radar antennas specifically includes:

[0017] Based on the Doppler frequency shift characteristics of the target echo signal of the radar antenna, a fitting calculation is performed with the sample Doppler frequency shift characteristics in the life detection signal feature library to determine the similarity fitting degree between the target echo signal of the radar antenna and the sample Doppler frequency shift characteristics;

[0018] At least one sample Doppler frequency shift feature whose similarity fitting degree is less than a preset value is selected and recorded as the initial fitting Doppler frequency shift feature;

[0019] Based on at least one initial fitting Doppler frequency shift feature corresponding to the target echo signals of multiple radar antennas, a sample Doppler frequency shift feature having the same sample body shape and physiological characteristics of the sample volunteer is screened out and recorded as a comprehensive Doppler frequency shift feature;

[0020] Determine whether there is only one comprehensive Doppler frequency shift feature. If so, record the comprehensive Doppler frequency shift feature as the final Doppler frequency shift feature. If not, determine the actual position of each comprehensive Doppler frequency shift feature in the actual environment based on the multi-point positioning method, and determine the final Doppler frequency shift feature from the comprehensive Doppler frequency shift features based on the actual environment state;

[0021] The sample body shape and physiological characteristics of the sample volunteers corresponding to the final Doppler frequency shift characteristics are determined as the physiological state of the living body.

[0022] Preferably, the method of determining the actual position of each integrated Doppler frequency shift feature in the actual environment based on multi-point positioning specifically includes:

[0023] From the life detection signal feature library, determine the distance of the measured integrated Doppler frequency shift feature of each radar antenna, and record it as the sample distance;

[0024] The radar antenna in the MIMO digital array is used as the radar antenna center, and the sample distance is used as a sphere, which is used as the positioning sphere of the radar antenna relative to the integrated Doppler frequency shift characteristics;

[0025] Based on the positioning sphere of all radar antennas relative to the integrated Doppler frequency shift characteristics, the intersection point is found, and the position of the intersection point is recorded as the actual position of the MIMO digital array relative to the integrated Doppler frequency shift characteristics in the actual environment.

[0026] Preferably, the step of determining and generating a rescue coordination plan for all living beings based on the rescue priority urgency of all living beings specifically includes:

[0027] Based on the positions of all living beings detected by the MIMO digital array, combined with the actual environment and rescue experience, determine at least one rescue route plan;

[0028] Determine the estimated rescue time for each living life under each rescue route plan;

[0029] Based on the estimated rescue time for each living being and the rescue priority urgency of all living beings, the rescue adaptation index of the rescue path plan is calculated through the plan fitting formula;

[0030] Determine the maximum rescue time required under the rescue path plan, which is recorded as the rescue timeliness index of the rescue path plan;

[0031] Based on the rescue adaptation index and rescue timeliness index of all rescue path solutions, the execution index of each rescue path solution is determined through the superior and inferior solution algorithm;

[0032] Filter out the rescue path plan corresponding to the maximum value of the plan execution index as the final rescue coordination plan;

[0033] Among them, the scheme fitting formula is specifically:

[0034]

[0035] Where Y i is the rescue priority urgency of the i-th living being, T i is the estimated rescue time for the i-th living life under the rescue path plan, Z fit It is the rescue adaptation index of the rescue path plan.

[0036] Preferably, the scheme execution index of each rescue path scheme is determined by the superior and inferior solution algorithm and specifically includes:

[0037] The maximum value among the rescue adaptation indexes of all rescue path solutions and the maximum value among the rescue timeliness indexes of all rescue path solutions are combined into the worst index group;

[0038] The minimum value of the rescue adaptation index of all rescue path solutions and the minimum value of the rescue timeliness index of all rescue path solutions are combined into an optimal index group;

[0039] Based on the superior and inferior solution formula, calculate the execution index of each rescue path solution;

[0040] The superiority and inferiority solution formula is specifically:

[0041]

[0042] In the formula, H j is the execution index of the j-th rescue path solution, Z fit j is the rescue adaptation index of the jth rescue path solution, S j is the rescue timeliness index of the j-th rescue path plan, Z fit max is the maximum value of the rescue adaptation index of all rescue path solutions, S max is the maximum value of the rescue timeliness index of all rescue path solutions, Z fit min is the minimum value of the rescue adaptation index of all rescue path solutions, S min It is the minimum value of the timely rescue index of all rescue path solutions.

[0043] Furthermore, a life detection signal recognition system based on a MIMO digital array is proposed, which is used to implement the life detection signal recognition method based on a MIMO digital array as described above, comprising:

[0044] A database module, wherein the database module is used to construct a life detection signal feature library;

[0045] A MIMO digital array module, wherein the MIMO digital array module is used to transmit electromagnetic waves based on multiple radar antennas of the MIMO digital array, and receive reflected echo signals, which are recorded as target echo signals;

[0046] A signal analysis module, the signal analysis module is electrically connected to the database module and the MIMO digital array module, and the signal analysis module is used to determine whether there is a Doppler frequency shift based on the target echo signals of multiple radar antennas, and if so, determine that there is a living life signal, and if not, determine that there is no living life signal;

[0047] A life state analysis module, the life state analysis module is electrically connected to the signal analysis module, and the life state analysis module is used to analyze the physiological state of the living body based on the Doppler frequency shift characteristics of the target echo signals of multiple radar antennas when there are living body life signals;

[0048] A rescue planning module, wherein the rescue planning module is electrically connected to the life status analysis module, and is used to evaluate the rescue priority urgency of each living being based on the physiological status of all living beings detected by the MIMO digital array and based on historical rescue experience, and at the same time, based on the rescue priority urgency of all living beings, determine and generate a rescue coordination plan for all living beings.

[0049] Optionally, the life status analysis module includes:

[0050] A matching analysis unit, wherein the matching analysis unit is used to perform fitting calculation based on the Doppler frequency shift feature of the target echo signal of the radar antenna and the sample Doppler frequency shift feature in the life detection signal feature library, determine the similarity and fit between the target echo signal of the radar antenna and the sample Doppler frequency shift feature, and screen out at least one sample Doppler frequency shift feature whose similarity and fit is less than a preset value, and record it as the initial fitting Doppler frequency shift feature;

[0051] A fusion analysis unit, the fusion analysis unit is used to screen out sample Doppler frequency shift features with the same sample body shape and sample volunteer's physiological characteristics based on at least one initial fitting Doppler frequency shift feature corresponding to target echo signals of multiple radar antennas, record them as comprehensive Doppler frequency shift features, and determine whether there is only one comprehensive Doppler frequency shift feature. If so, record the comprehensive Doppler frequency shift feature as the final Doppler frequency shift feature. If not, determine the actual position of each comprehensive Doppler frequency shift feature in the actual environment based on a multi-point positioning method, and determine the final Doppler frequency shift feature from the comprehensive Doppler frequency shift features based on the actual environment state, and determine the sample body shape and sample volunteer's physiological characteristics corresponding to the final Doppler frequency shift feature as the physiological state of the living body.

[0052] Optionally, the rescue planning module includes:

[0053] A priority adaptation unit, the priority adaptation unit is used to calculate the rescue adaptation index of the rescue path solution through a solution fitting formula based on the estimated rescue time of each living life and the rescue priority urgency of all living lives;

[0054] A plan timeliness analysis unit, the plan timeliness analysis unit is used to determine the maximum rescue time required under the rescue path plan, which is recorded as the rescue timeliness index of the rescue path plan;

[0055] The advantages and disadvantages analysis unit is used to determine the scheme execution index of each rescue path scheme based on the rescue adaptation index and rescue timeliness index of all rescue path schemes through a pros and cons solution algorithm, and screen out the rescue path scheme corresponding to the maximum value of the scheme execution index as the final rescue coordination plan.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] The present invention proposes a life detection signal recognition solution based on MIMO digital array. By constructing a life detection signal feature library containing multiple physiological characteristics, during actual monitoring, multiple radar antennas of the MIMO digital array transmit electromagnetic waves and receive reflected echo signals, analyze the frequency shift characteristics of the Doppler effect caused by breathing and heartbeat in the echo signals, and comprehensively evaluate the Doppler frequency shift characteristics in the echo signals received by multiple radar antennas and the data in the life detection signal feature library. It effectively realizes high-precision detection of human targets in a static state, and provides a more efficient and accurate non-contact life detection solution for disaster relief, medical monitoring and other fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 Flowchart of the life detection signal recognition method based on MIMO digital array proposed in this scheme;

[0059] Figure 2 This is a flow chart of the method for building a life detection signal feature library in this scheme;

[0060] Figure 3 This is a flow chart of the method for analyzing the physiological state of a living being in this scheme;

[0061] Figure 4 A flow chart of a method for determining the actual position of each integrated Doppler frequency shift feature in an actual environment in the present solution;

[0062] Figure 5 A flow chart of the method for generating a coordinated rescue plan for all living beings determined in this plan;

[0063] Figure 6 A flow chart of the method for determining the program execution index of each rescue path program in this program;

[0064] Figure 7 The block diagram of the life detection signal recognition system based on MIMO digital array proposed in this scheme;

[0065] Figure 8 This is a schematic diagram of the computer-readable storage medium structure in this solution. DETAILED DESCRIPTION

[0066] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0067] Reference Figure 1 As shown, a life detection signal recognition method based on a MIMO digital array includes:

[0068] Establish a life detection signal feature library;

[0069] Multiple radar antennas based on the MIMO digital array transmit electromagnetic waves and receive the reflected echo signals, which are recorded as target echo signals;

[0070] Determine whether there is a Doppler frequency shift based on the target echo signals of multiple radar antennas, and if so, determine that there is a living life signal, and if not, determine that there is no living life signal;

[0071] If there is a living body’s life signal, the physiological state of the living body is analyzed based on the Doppler frequency shift characteristics of the target echo signals from multiple radar antennas;

[0072] Based on the physiological status of all living beings detected by the MIMO digital array and historical rescue experience, the rescue priority urgency of each living being is assessed;

[0073] Based on the rescue priority and urgency of all living lives, a coordinated rescue plan for all living lives is determined and generated.

[0074] This solution builds a life detection signal feature library that includes multiple physiological characteristics. During actual monitoring, multiple radar antennas of the MIMO digital array transmit electromagnetic waves and receive reflected echo signals. The frequency shift characteristics of the Doppler effect caused by breathing and heartbeat in the echo signals are analyzed, and the Doppler frequency shift characteristics in the echo signals received by multiple radar antennas are comprehensively evaluated with the data in the life detection signal feature library. This effectively achieves high-precision detection of human targets in a static state.

[0075] Reference Figure 2 As shown, the establishment of a life detection signal feature library specifically includes:

[0076] Based on historical rescue experience, the actual postures of all rescued persons in actual rescues are collected and recorded as sample postures;

[0077] The Doppler frequency shift characteristics of the echo signals of the sample volunteers in different sample postures are collected by using a MIMO digital array, and recorded as sample Doppler frequency shift characteristics;

[0078] The sample Doppler frequency shift characteristics of multiple sample volunteers with different physiological characteristics at different distances are collected, and a one-to-one correspondence is established between all sample Doppler frequency shift characteristics and distance, sample body shape and physiological characteristics of sample volunteers to form a life detection signal feature library.

[0079] Life detection using the Doppler effect is mainly based on radar technology. It detects the existence of life and its physiological state by emitting electromagnetic waves and receiving echo signals reflected by life, and analyzing the Doppler frequency shift in the signal. The Doppler effect causes the frequency of the received echo signal to change when there is relative motion between the radar wave source and the life. Physiological activities such as breathing and heartbeat of life can cause tiny movements on the body surface. These movements can cause tiny changes in the frequency of the reflected signal, which can be captured and analyzed by the radar system.

[0080] Reference Figure 3 As shown, based on the Doppler frequency shift characteristics of the target echo signals of multiple radar antennas, the physiological state of the living body is analyzed, including:

[0081] Based on the Doppler frequency shift characteristics of the target echo signal of the radar antenna, a fitting calculation is performed with the sample Doppler frequency shift characteristics in the life detection signal feature library to determine the similarity fitting degree between the target echo signal of the radar antenna and the sample Doppler frequency shift characteristics;

[0082] At least one sample Doppler frequency shift feature whose similarity fitting degree is less than a preset value is selected and recorded as the initial fitting Doppler frequency shift feature;

[0083] Based on at least one initial fitting Doppler frequency shift feature corresponding to the target echo signals of multiple radar antennas, a sample Doppler frequency shift feature having the same sample body shape and physiological characteristics of the sample volunteer is screened out and recorded as a comprehensive Doppler frequency shift feature;

[0084] Determine whether there is only one comprehensive Doppler frequency shift feature. If so, record the comprehensive Doppler frequency shift feature as the final Doppler frequency shift feature. If not, determine the actual position of each comprehensive Doppler frequency shift feature in the actual environment based on the multi-point positioning method, and determine the final Doppler frequency shift feature from the comprehensive Doppler frequency shift features based on the actual environment state;

[0085] The sample body shape and physiological characteristics of the sample volunteers corresponding to the final Doppler frequency shift characteristics are determined as the physiological state of the living body.

[0086] In the fields of disaster relief, medical monitoring, anti-terrorism investigation, etc., life detectors using the Doppler effect can penetrate obstacles (such as ruins, walls, etc.) to detect trapped or hidden life forms, providing key information for rescue operations. At the same time, by monitoring the life form's breathing, heartbeat and other physiological parameters, its vital signs can be evaluated.

[0087] Reference Figure 4 As shown, based on the multi-point positioning method, determining the actual position of each integrated Doppler frequency shift feature in the actual environment specifically includes:

[0088] From the life detection signal feature library, determine the distance of the measured integrated Doppler frequency shift feature of each radar antenna, and record it as the sample distance;

[0089] The radar antenna in the MIMO digital array is used as the radar antenna center, and the sample distance is used as a sphere, which is used as the positioning sphere of the radar antenna relative to the integrated Doppler frequency shift characteristics;

[0090] Based on the positioning sphere of all radar antennas relative to the integrated Doppler frequency shift characteristics, the intersection point is found, and the position of the intersection point is recorded as the actual position of the MIMO digital array relative to the integrated Doppler frequency shift characteristics in the actual environment.

[0091] The influence of distance on the Doppler effect is mainly reflected in two aspects: first, the distance between the sender and the receiver directly affects the frequency change amplitude caused by the Doppler effect; second, the attenuation of the wave when it propagates in the medium is related to the distance, and this attenuation will also be manifested in the form of frequency shift, but this frequency shift is different from the motion frequency shift and is usually called attenuation frequency shift. When the distance between the sender and the receiver is close, the frequency change caused by the Doppler effect is relatively small. This is because when the distance is very close, the time interval between the received wave peaks is close to the transmitted frequency, so even if there is relative motion, the frequency change will not be large. On the contrary, when the distance is far, due to the influence of various factors in the wave propagation and reception process (such as medium characteristics, wave speed changes, etc.), the frequency change caused by the Doppler effect may be more obvious.

[0092] Therefore, in practical applications, different body surface change amplitudes at different distances may cause similar Doppler frequency shift characteristics. Based on this, this scheme uses radar antennas at different positions to perform comprehensive multi-point joint ranging relative to a single sample Doppler frequency shift characteristic with the same sample body shape and physiological characteristics of sample volunteers, which can achieve accurate matching and identification of the sample Doppler frequency shift characteristics.

[0093] Reference Figure 5 As shown, based on the rescue priority and urgency of all living lives, the rescue coordination plan for all living lives is determined to include:

[0094] Based on the positions of all living beings detected by the MIMO digital array, combined with the actual environment and rescue experience, determine at least one rescue route plan;

[0095] Determine the estimated rescue time for each living life under each rescue route plan;

[0096] Based on the estimated rescue time for each living being and the rescue priority urgency of all living beings, the rescue adaptation index of the rescue path plan is calculated through the plan fitting formula;

[0097] Determine the maximum rescue time required under the rescue path plan, which is recorded as the rescue timeliness index of the rescue path plan;

[0098] Based on the rescue adaptation index and rescue timeliness index of all rescue path solutions, the execution index of each rescue path solution is determined through the superior and inferior solution algorithm;

[0099] Filter out the rescue path plan corresponding to the maximum value of the plan execution index as the final rescue coordination plan;

[0100] Among them, the scheme fitting formula is specifically:

[0101]

[0102] Where Y i is the rescue priority urgency of the i-th living being, T i is the estimated rescue time for the i-th living life under the rescue path plan, Z fit It is the rescue adaptation index of the rescue path plan.

[0103] Reference Figure 6 As shown in the figure, through the superior and inferior solution algorithm, the execution indicators of each rescue path solution are determined to include:

[0104] The maximum value among the rescue adaptation indexes of all rescue path solutions and the maximum value among the rescue timeliness indexes of all rescue path solutions are combined into the worst index group;

[0105] The minimum value of the rescue adaptation index of all rescue path solutions and the minimum value of the rescue timeliness index of all rescue path solutions are combined into an optimal index group;

[0106] Based on the superior and inferior solution formula, calculate the execution index of each rescue path solution;

[0107] The specific formula for the superior and inferior solution is:

[0108]

[0109] In the formula, H j is the execution index of the j-th rescue path solution, Z fit j is the rescue adaptation index of the jth rescue path solution, S j is the rescue timeliness index of the j-th rescue path plan, Z fitmax is the maximum value of the rescue adaptation index of all rescue path solutions, S max is the maximum value of the rescue timeliness index of all rescue path solutions, Z fit min is the minimum value of the rescue adaptation index of all rescue path solutions, S min It is the minimum value of the timely rescue index of all rescue path solutions.

[0110] The best-case solution algorithm is a commonly used multi-criteria decision analysis method used to evaluate and compare a series of alternative solutions to find the optimal solution. In this solution, a comprehensive evaluation of the rescue path solution is performed under the two dimensions of rescue adaptation index and rescue timeliness index under multiple rescue solutions, which effectively realizes the efficient identification and generation of the optimal rescue path solution, ensures the efficient and rapid execution of rescue tasks, and reduces the loss of life and property.

[0111] Further, see Figure 7 As shown, based on the same inventive concept as the above-mentioned life detection signal recognition method based on MIMO digital array, this solution proposes a life detection signal recognition system based on MIMO digital array, including:

[0112] A database module, which is used to build a life detection signal feature library;

[0113] MIMO digital array module, the MIMO digital array module is used to transmit electromagnetic waves based on multiple radar antennas of the MIMO digital array, and receive reflected echo signals, which are recorded as target echo signals;

[0114] A signal analysis module, the signal analysis module is electrically connected to the database module and the MIMO digital array module, and the signal analysis module is used to determine whether there is a Doppler frequency shift based on the target echo signals of multiple radar antennas, and if so, it is determined that there is a living life signal, and if not, it is determined that there is no living life signal;

[0115] A life state analysis module, the life state analysis module is electrically connected to the signal analysis module, and the life state analysis module is used to analyze the physiological state of the living body based on the Doppler frequency shift characteristics of the target echo signals of multiple radar antennas when there are living body life signals;

[0116] The rescue planning module is electrically connected to the life status analysis module. The rescue planning module is used to evaluate the rescue priority urgency of each living being based on the physiological status of all living beings detected by the MIMO digital array and based on historical rescue experience. At the same time, based on the rescue priority urgency of all living beings, a rescue coordination plan for all living beings is determined and generated.

[0117] The life status analysis module includes:

[0118] A matching analysis unit, the matching analysis unit is used to perform fitting calculation based on the Doppler frequency shift feature of the target echo signal of the radar antenna and the sample Doppler frequency shift feature in the life detection signal feature library, determine the similarity and fit between the target echo signal of the radar antenna and the sample Doppler frequency shift feature, and screen out at least one sample Doppler frequency shift feature whose similarity and fit is less than a preset value, which is recorded as the initial fitting Doppler frequency shift feature;

[0119] A fusion analysis unit is used to screen out sample Doppler frequency shift features having the same sample body shape and physiological characteristics of sample volunteers based on at least one initial fitting Doppler frequency shift feature corresponding to target echo signals of multiple radar antennas, record the features as comprehensive Doppler frequency shift features, and determine whether there is only one comprehensive Doppler frequency shift feature. If so, record the comprehensive Doppler frequency shift feature as the final Doppler frequency shift feature. If not, determine the actual position of each comprehensive Doppler frequency shift feature in the actual environment based on multi-point positioning, and determine the final Doppler frequency shift feature from the comprehensive Doppler frequency shift features based on the actual environment state, and determine the sample body shape and the physiological characteristics of the sample volunteers corresponding to the final Doppler frequency shift feature as the physiological state of the living body.

[0120] The rescue planning module includes:

[0121] The priority adaptation unit is used to calculate the rescue adaptation index of the rescue path plan through a plan fitting formula based on the estimated rescue time of each living life and the rescue priority urgency of all living lives;

[0122] A plan timeliness analysis unit, which is used to determine the maximum rescue time required under the rescue path plan, recorded as the rescue timeliness index of the rescue path plan;

[0123] The pros and cons analysis unit is used to determine the scheme execution index of each rescue path scheme based on the rescue adaptation index and rescue timeliness index of all rescue path schemes through the pros and cons solution algorithm, and screen out the rescue path scheme corresponding to the maximum value of the scheme execution index as the final rescue coordination plan.

[0124] The process of using the above system is as follows:

[0125] Step 1: The MIMO digital array module transmits electromagnetic waves based on multiple radar antennas of the MIMO digital array, and receives the reflected echo signals, which are recorded as target echo signals;

[0126] Step 2: The signal analysis module determines whether there is a Doppler frequency shift based on the target echo signals of multiple radar antennas. If so, it is determined that there is a living life signal; if not, it is determined that there is no living life signal;

[0127] Step 3: The matching analysis unit performs fitting calculation based on the Doppler frequency shift characteristics of the target echo signal of the radar antenna and the sample Doppler frequency shift characteristics in the life detection signal feature library, determines the similarity and fit between the target echo signal of the radar antenna and the sample Doppler frequency shift characteristics, and selects at least one sample Doppler frequency shift characteristic whose similarity and fit is less than a preset value, which is recorded as the initial fitting Doppler frequency shift characteristic;

[0128] Step 4: The fusion analysis unit selects sample Doppler frequency shift features with the same sample body shape and sample volunteer's physiological characteristics based on at least one initial fitting Doppler frequency shift feature corresponding to the target echo signals of multiple radar antennas, records them as comprehensive Doppler frequency shift features, and determines whether there is only one comprehensive Doppler frequency shift feature. If so, the comprehensive Doppler frequency shift feature is recorded as the final Doppler frequency shift feature. If not, the actual position of each comprehensive Doppler frequency shift feature in the actual environment is determined based on the multi-point positioning method, and the final Doppler frequency shift feature is determined from the comprehensive Doppler frequency shift features based on the actual environment state, and the sample body shape and sample volunteer's physiological characteristics corresponding to the final Doppler frequency shift feature are determined as the physiological state of the living body;

[0129] Step 5: The priority adaptation unit calculates the rescue adaptation index of the rescue path plan through the plan fitting formula based on the estimated rescue time of each living life and the rescue priority urgency of all living lives;

[0130] Step 6: The plan timeliness analysis unit determines the maximum rescue time required under the rescue path plan, which is recorded as the rescue timeliness index of the rescue path plan;

[0131] Step 7: The pros and cons analysis unit determines the execution index of each rescue path plan based on the rescue adaptation index and rescue timeliness index of all rescue path plans through the pros and cons solution algorithm, and selects the rescue path plan corresponding to the maximum value of the plan execution index as the final rescue coordination plan.

[0132] Figure 8 Schematic diagram of a computer-readable storage medium structure provided by an embodiment of the present application. Figure 8As shown, a computer-readable storage medium 600 according to an embodiment of the present application is shown. A computer-readable program is stored on the computer-readable storage medium 600. When the computer-readable program is executed by the processor, a life detection signal recognition method based on a MIMO digital array according to an embodiment of the present application described with reference to the above figures can be executed. The storage medium 600 includes, but is not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory (cache), etc. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0133] In summary, the advantages of the present invention are: effectively realizing high-precision detection of human targets in a stationary state, and providing a more efficient and accurate non-contact life detection solution for disaster relief, medical monitoring and other fields.

[0134] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for identifying life detection signals based on a MIMO digital array, characterized in that: include: Establish a life detection signal feature library; Multiple radar antennas based on the MIMO digital array transmit electromagnetic waves and receive the reflected echo signals, which are recorded as target echo signals; Determine whether there is a Doppler frequency shift based on the target echo signals of multiple radar antennas, and if so, determine that there is a living life signal, and if not, determine that there is no living life signal; If there is a living body signal, a fitting calculation is performed based on the Doppler frequency shift characteristics of the target echo signal of the radar antenna and the sample Doppler frequency shift characteristics in the life detection signal feature library to determine the similarity fitting degree between the target echo signal of the radar antenna and the sample Doppler frequency shift characteristics; At least one sample Doppler frequency shift feature whose similarity fitting degree is less than a preset value is selected and recorded as the initial fitting Doppler frequency shift feature; Based on at least one initial fitting Doppler frequency shift feature corresponding to the target echo signals of multiple radar antennas, a sample Doppler frequency shift feature having the same sample body shape and physiological characteristics of the sample volunteer is screened out and recorded as a comprehensive Doppler frequency shift feature; Determine whether there is only one comprehensive Doppler frequency shift feature. If so, record the comprehensive Doppler frequency shift feature as the final Doppler frequency shift feature. If not, determine the actual position of each comprehensive Doppler frequency shift feature in the actual environment based on the multi-point positioning method, and determine the final Doppler frequency shift feature from the comprehensive Doppler frequency shift features based on the actual environment state; Determine the sample body shape and the physiological characteristics of the sample volunteer corresponding to the final Doppler frequency shift characteristics as the physiological state of the living body; Based on the physiological status of all living beings detected by the MIMO digital array and historical rescue experience, the rescue priority urgency of each living being is assessed; Based on the rescue priority and urgency of all living lives, a coordinated rescue plan for all living lives is determined and generated.

2. The method for identifying life detection signals based on a MIMO digital array according to claim 1, characterized in that: The said building of the life detection signal feature library specifically comprises: Based on historical rescue experience, the actual postures of all rescued persons in actual rescues are collected and recorded as sample postures; The Doppler frequency shift characteristics of the echo signals of the sample volunteers in different sample postures are collected by using a MIMO digital array, and recorded as sample Doppler frequency shift characteristics; The sample Doppler frequency shift characteristics of multiple sample volunteers with different physiological characteristics at different distances are collected, and a one-to-one correspondence is established between all sample Doppler frequency shift characteristics and distance, sample body shape and physiological characteristics of sample volunteers to form a life detection signal feature library.

3. The method for identifying life detection signals based on a MIMO digital array according to claim 2, characterized in that: The method of determining the actual position of each integrated Doppler frequency shift feature in the actual environment based on multi-point positioning specifically includes: From the life detection signal feature library, determine the distance of the measured integrated Doppler frequency shift feature of each radar antenna, and record it as the sample distance; The radar antenna in the MIMO digital array is used as the radar antenna center, and the sample distance is used as a sphere, which is used as the positioning sphere of the radar antenna relative to the integrated Doppler frequency shift characteristics; Based on the positioning sphere of all radar antennas relative to the integrated Doppler frequency shift characteristics, the intersection point is found, and the position of the intersection point is recorded as the actual position of the MIMO digital array relative to the integrated Doppler frequency shift characteristics in the actual environment.

4. The method for identifying life detection signals based on a MIMO digital array according to claim 3, characterized in that: The determination and generation of a rescue coordination plan for all living beings based on the rescue priority urgency of all living beings specifically includes: Based on the positions of all living beings detected by the MIMO digital array, combined with the actual environment and rescue experience, determine at least one rescue route plan; Determine the estimated rescue time for each living life under each rescue route plan; Based on the estimated rescue time for each living being and the rescue priority urgency of all living beings, the rescue adaptation index of the rescue path plan is calculated through the plan fitting formula; Determine the maximum rescue time required under the rescue path plan, which is recorded as the rescue timeliness index of the rescue path plan; Based on the rescue adaptation index and rescue timeliness index of all rescue path solutions, the execution index of each rescue path solution is determined through the superior and inferior solution algorithm; Filter out the rescue path plan corresponding to the maximum value of the plan execution index as the final rescue coordination plan; The scheme fitting formula is specifically: In the formula, is the rescue priority urgency of the i-th living being, is the estimated rescue time for the i-th living life under the rescue path plan, It is the rescue adaptation index of the rescue path plan.

5. The method for identifying life detection signals based on a MIMO digital array according to claim 4, characterized in that: The solution execution index of each rescue path solution determined by the superior and inferior solution algorithm specifically includes: The maximum value among the rescue adaptation indexes of all rescue path solutions and the maximum value among the rescue timeliness indexes of all rescue path solutions are combined into the worst index group; The minimum value of the rescue adaptation index of all rescue path solutions and the minimum value of the rescue timeliness index of all rescue path solutions are combined into an optimal index group; Based on the superior and inferior solution formula, calculate the execution index of each rescue path solution; The superiority and inferiority solution formula is specifically: In the formula, is the execution index of the j-th rescue path solution, is the rescue adaptation index of the jth rescue path solution, is the rescue timeliness index of the j-th rescue path plan, is the maximum value of the rescue adaptation index of all rescue path solutions, is the maximum value of the timely rescue index of all rescue path solutions, is the minimum value of the rescue adaptation index of all rescue path solutions, It is the minimum value of the timely rescue index of all rescue path solutions.

6. A life detection signal recognition system based on MIMO digital array, characterized in that: The method for realizing the life detection signal recognition method based on the MIMO digital array according to any one of claims 1 to 5 comprises: A database module, wherein the database module is used to construct a life detection signal feature library; A MIMO digital array module, wherein the MIMO digital array module is used to transmit electromagnetic waves based on multiple radar antennas of the MIMO digital array, and receive reflected echo signals, which are recorded as target echo signals; A signal analysis module, the signal analysis module is electrically connected to the database module and the MIMO digital array module, and the signal analysis module is used to determine whether there is a Doppler frequency shift based on the target echo signals of multiple radar antennas, and if so, determine that there is a living life signal, and if not, determine that there is no living life signal; A life state analysis module, the life state analysis module is electrically connected to the signal analysis module, and the life state analysis module is used to analyze the physiological state of the living body based on the Doppler frequency shift characteristics of the target echo signals of multiple radar antennas when there are living body life signals; A rescue planning module, wherein the rescue planning module is electrically connected to the life status analysis module, and is used to evaluate the rescue priority urgency of each living being based on the physiological status of all living beings detected by the MIMO digital array and based on historical rescue experience, and at the same time, based on the rescue priority urgency of all living beings, determine and generate a rescue coordination plan for all living beings.

7. A life detection signal recognition system based on MIMO digital array according to claim 6, characterized in that: The life status analysis module includes: A matching analysis unit, wherein the matching analysis unit is used to perform fitting calculation based on the Doppler frequency shift feature of the target echo signal of the radar antenna and the sample Doppler frequency shift feature in the life detection signal feature library, determine the similarity and fit between the target echo signal of the radar antenna and the sample Doppler frequency shift feature, and screen out at least one sample Doppler frequency shift feature whose similarity and fit is less than a preset value, and record it as the initial fitting Doppler frequency shift feature; A fusion analysis unit, the fusion analysis unit is used to screen out sample Doppler frequency shift features with the same sample body shape and sample volunteer's physiological characteristics based on at least one initial fitting Doppler frequency shift feature corresponding to target echo signals of multiple radar antennas, record them as comprehensive Doppler frequency shift features, and determine whether there is only one comprehensive Doppler frequency shift feature. If so, record the comprehensive Doppler frequency shift feature as the final Doppler frequency shift feature. If not, determine the actual position of each comprehensive Doppler frequency shift feature in the actual environment based on a multi-point positioning method, and determine the final Doppler frequency shift feature from the comprehensive Doppler frequency shift features based on the actual environment state, and determine the sample body shape and sample volunteer's physiological characteristics corresponding to the final Doppler frequency shift feature as the physiological state of the living body.

8. The life detection signal recognition system based on MIMO digital array according to claim 7, characterized in that: The rescue planning module includes: A priority adaptation unit, the priority adaptation unit is used to calculate the rescue adaptation index of the rescue path solution through a solution fitting formula based on the estimated rescue time of each living life and the rescue priority urgency of all living lives; A plan timeliness analysis unit, the plan timeliness analysis unit is used to determine the maximum rescue time required under the rescue path plan, which is recorded as the rescue timeliness index of the rescue path plan; The advantages and disadvantages analysis unit is used to determine the scheme execution index of each rescue path scheme based on the rescue adaptation index and rescue timeliness index of all rescue path schemes through a pros and cons solution algorithm, and screen out the rescue path scheme corresponding to the maximum value of the scheme execution index as the final rescue coordination plan.

9. A computer-readable storage medium, characterized in that: A computer-readable program is stored thereon, and when the computer-readable program is called, the life detection signal recognition method based on the MIMO digital array as described in any one of claims 1 to 5 is executed.

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