Target object position prediction method, device, system and equipment and storage medium

Abstract

The embodiment of the invention provides a target object position prediction method, device, system and equipment and a storage medium, and the method comprises the steps: extracting a target sound signal generated by a target object from environment sound signals when the environment sound signals transmitted by a plurality of acoustic positioning sensors are received; calculating to obtain a difference frequency signal of every two target sound signals; acquiring a grid map of the target area; according to all the difference frequency signals, determining the probability that the target object exists in each grid in the grid map, and updating to obtain the grid map recording the probability that the target object exists in each grid; and determining the position of the target object according to the updated grid map.

Description

Technical Field

[0001] The present invention relates to the technical field of position prediction, and in particular to a method, device, system, equipment and storage medium for predicting the position of a target object. Background Art

[0002] Although the widespread use of civil drones can bring a lot of entertainment to residents, it also facilitates the infiltration of reconnaissance drones that are similar in appearance to civil drones. Therefore, the use of drones will bring certain security risks to society.

[0003] For social security reasons, it is necessary to counter unauthorized drones, and to effectively counter drones, drones need to be located. At present, drones are generally located through positioning methods such as radar or radio direction finding, but because the electromagnetic characteristics of reconnaissance drones are weaker than those of civilian drones, and because the number of reconnaissance drones is also relatively large, the target positioning method requires a lot of investment costs to deploy radar or radio direction finding devices, and the individual costs of radar and radio direction finding devices are relatively high, which will result in a relatively high cost of the entire positioning system, but the effect is relatively low.

[0004] Therefore, the current positioning method not only makes the positioning results easily affected by the electromagnetic characteristics of reconnaissance drones, but also has a poor cost-effectiveness when positioning a large number of reconnaissance drones, and the number of reconnaissance drones that can be dealt with is often not large. Summary of the invention

[0005] In view of this, an object of the present invention is to provide a method, device, system, equipment and storage medium for predicting the position of a target object.

[0006] In order to achieve the above purpose, the technical solution adopted by the embodiment of the present invention is as follows:

[0007] According to a first aspect of an embodiment of the present invention, a method for predicting the position of a target object is provided, which is applied to a monitoring center, wherein the monitoring center is used to communicate with a plurality of acoustic positioning sensors arranged at different positions in a target area; the plurality of acoustic positioning sensors are used to simultaneously receive ambient sound signals in the target area, and the monitoring range of the plurality of acoustic positioning sensors covers the target area; the method comprises:

[0008] When receiving the ambient sound signals sent by the plurality of acoustic positioning sensors, extracting the target sound signal generated by the target object from the ambient sound signals;

[0009] Calculate and obtain the difference frequency signal between every two target sound signals;

[0010] Obtaining a grid map of the target area;

[0011] Determine the probability of the target object existing in each grid in the grid map according to all the difference frequency signals, and update the grid map recording the probability of the target object existing in each grid;

[0012] The position of the target object is determined according to the updated grid map.

[0013] According to a second aspect of an embodiment of the present invention, a target position prediction device is provided, which is applied to a monitoring center, wherein the monitoring center is used to communicate with a plurality of acoustic positioning sensors arranged at different positions in a target area; the plurality of acoustic positioning sensors are used to simultaneously receive ambient sound signals in the target area, and the monitoring range of the plurality of acoustic positioning sensors covers the target area; the device comprises:

[0014] The extraction module is configured to: extract the target sound signal generated by the target object from the ambient sound signal when receiving the ambient sound signal sent by the plurality of acoustic positioning sensors;

[0015] The calculation module is configured to: calculate and obtain a difference frequency signal between every two target sound signals;

[0016] An acquisition module is configured to: acquire a grid map of the target area;

[0017] A processing module is configured to: determine the probability of the target object existing in each grid in the grid map according to all the difference frequency signals, and update the grid map recording the probability of the target object existing in each grid;

[0018] The determination module is configured to: determine the position of the target object according to the updated grid map.

[0019] A third aspect of an embodiment of the present invention provides a target position prediction system, including:

[0020] Broadcast center, used to broadcast synchronous sound signals;

[0021] A plurality of acoustic positioning sensors are arranged at different positions in the target area and are used to simultaneously receive the synchronous sound signal broadcast by the broadcast center and the ambient sound signal in the target area, and the monitoring range of the plurality of acoustic positioning sensors covers the target area;

[0022] and a monitoring center, which is used to communicate with the multiple acoustic positioning sensors and determine the position of the target object in the target area based on the synchronous acoustic signal, or the synchronous acoustic signal and the ambient acoustic signal by executing the target object position prediction method provided by the first aspect.

[0023] According to a fourth aspect of an embodiment of the present invention, an electronic device is provided, comprising a processor and a memory, wherein the memory stores machine executable instructions that can be executed by the processor, and the processor can execute the machine executable instructions to implement the target object position prediction method provided in the first aspect above.

[0024] According to a fifth aspect of an embodiment of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the target position prediction method provided in the first aspect is implemented.

[0025] The target position prediction method, device, system, equipment and storage medium provided by the embodiments of the present invention utilize multiple acoustic positioning sensors to monitor the ambient sound signals in the target area, and extract the target sound signal generated by the target object from the ambient sound signal based on the sound characteristics generated by the target object to be monitored during operation, and then use the target sound signal to calculate the probability of the existence of the target object in each grid in the grid map of the target area, and then determine the position of the target object based on the grid map with probability. Therefore, on the one hand, since the present invention locates the target object by utilizing the sound signal generated by the target object itself, rather than by emitting electromagnetic waves or sound waves to achieve the positioning of the target object, even if the electromagnetic characteristics of the target object are very weak, it will not have an adverse effect on the positioning result of the present invention, and is therefore conducive to improving the positioning accuracy of the target object with weak electromagnetic characteristics. On the other hand, in the process of locating the target object, the target object position is not directly solved based on the difference frequency signal to obtain a unique result. Instead, the probability of the target object being in each grid is calculated based on each grid in the grid map. It can be seen that for each grid, as long as the corresponding probability reaches a size that can characterize the existence of the target object, it can be considered that the credibility of the existence of the target object is relatively high. In this way, if there are multiple grids with high credibility of the existence of targets, it means that there may be multiple targets. This can not only realize the positioning of a single target object, but also the positioning of multiple targets. It can well cope with the positioning needs of a large number of targets. It can be seen that relatively good results can be achieved without using a costly positioning system.

[0026] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 A structural block diagram of an electronic device provided by an embodiment of the present invention is shown;

[0029] Figure 2 A flow chart of a method for predicting the position of a target object provided by an embodiment of the present invention is shown;

[0030] Figure 3 A functional module diagram of a target position prediction device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0031] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0032] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0033] It should be noted that relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0034] In order to solve the technical problems that the positioning results of the traditional positioning method are easily affected by the electromagnetic characteristics of the target object, and when positioning a large number of targets, there is a poor cost-effectiveness, and the number of reconnaissance drones that can be dealt with is often small, the present invention provides a target position prediction method, which uses multiple acoustic positioning sensors to monitor the ambient sound signal in the target area, and extracts the target sound signal generated by the target object from the ambient sound signal based on the sound characteristics generated by the target object to be monitored during operation, and then uses the target sound signal to calculate the probability of the existence of the target object in each grid in the grid map of the target area, and then determines the position of the target object based on the grid map with probability. Therefore, on the one hand, since the present invention locates the target object by using the sound signal generated by the target object itself, rather than by emitting electromagnetic waves or sound waves to achieve the positioning of the target object, even if the electromagnetic characteristics of the target object are very weak, it will not cause adverse effects on the positioning results of the present invention, so it is conducive to improving the positioning accuracy of the target object with weak electromagnetic characteristics. On the other hand, in the process of locating the target object, the target object position is not directly solved based on the difference frequency signal to obtain a unique result. Instead, the probability of the target object being in each grid is calculated based on each grid in the grid map. It can be seen that for each grid, as long as the corresponding probability reaches a size that can characterize the existence of the target object, it can be considered that the credibility of the existence of the target object is relatively high. In this way, if there are multiple grids with high credibility of the existence of targets, it means that there may be multiple targets. This can not only realize the positioning of a single target object, but also the positioning of multiple targets. It can well cope with the positioning needs of a large number of targets. It can be seen that relatively good results can be achieved without using a costly positioning system.

[0035] The target position prediction method provided by the present invention can be applied to electronic devices. Figure 1 , is a block diagram of the structure of an electronic device. The electronic device 100 includes a memory 110, a processor 120 and a communication module 130. The memory 110, the processor 120 and the communication module 130 are electrically connected to each other directly or indirectly to achieve data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines.

[0036] The memory is used to store programs or data. The memory may be, but is not limited to, a random access memory (RAM), a read only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), etc.

[0037] The processor is used to read / write data or programs stored in the memory and execute corresponding functions.

[0038] The communication module is used to establish a communication connection between the electronic device and other communication terminals through a network, and is used to send and receive data through the network.

[0039] It should be understood that Figure 1 The structure shown is only a schematic diagram of the structure of the electronic device, and the electronic device may also include Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown. Figure 1 Each component shown in the figure can be implemented by hardware, software or a combination thereof.

[0040] As an application example of an electronic device, it can be used as a monitoring center in a target position prediction system provided by an embodiment of the present invention. The target position prediction system may include:

[0041] Broadcast center, used to broadcast synchronous sound signals;

[0042] A plurality of acoustic positioning sensors are arranged at different positions in the target area and are used to simultaneously receive the synchronous acoustic signal broadcast by the broadcast center and the ambient acoustic signal in the target area, or to only receive the ambient acoustic signal in the target area;

[0043] and a monitoring center, which is used to communicate with the multiple acoustic positioning sensors and determine the position of the target object in the target area based on the synchronous acoustic signal, or the synchronous acoustic signal and the ambient acoustic signal by executing the target object position prediction method provided by an embodiment of the present invention.

[0044] In the above, the broadcast center can be a broadcast base station deployed in the target area, or a device with broadcasting function carried by users in the target area, such as a mobile phone, tablet, laptop or music player, but not limited thereto.

[0045] The target area can be understood as an area that needs to be monitored for security. For example, when the target object is a reconnaissance drone, the target area can be an area that is prohibited for the reconnaissance drone to enter. Based on this, when multiple acoustic positioning sensors are deployed, a sufficient number of acoustic positioning sensors can be deployed according to the size of the target area and the effective monitoring range of the multiple acoustic positioning sensors, so that the effective monitoring range formed by all the deployed acoustic positioning sensors can cover the target area.

[0046] In addition, when there is no delay or the delay in data transmission between multiple acoustic positioning sensors and the monitoring center can be ignored, in order to simplify the structural composition of the target object position prediction system and reduce the hardware cost of the target object position prediction system, in some embodiments, the broadcast center in the target object position prediction system can be removed.

[0047] The following combination Figure 2 The target position prediction method provided by the embodiment of the present invention is described. Figure 2 : is a flow chart of a target position prediction method provided by an embodiment of the present invention, the target position prediction method is applied to the above-mentioned monitoring center, and the method includes:

[0048] In step S100, when the ambient sound signals sent by the plurality of acoustic positioning sensors are received, a target sound signal generated by the target object is extracted from the ambient sound signal;

[0049] In step S200, a difference frequency signal between every two target sound signals is calculated;

[0050] In step S300, a grid map of the target area is obtained;

[0051] In step S400, the probability of the target object existing in each grid in the grid map is determined according to all the difference frequency signals, and the grid map recording the probability of the target object existing in each grid is updated;

[0052] In step S500, the position of the target object is determined according to the updated grid map.

[0053] After the target location prediction system is deployed in the target area, a grid map of the target area can be established according to the set coordinate system. In the grid map, the size of each grid can be consistent, so as to facilitate the subsequent estimation of the probability of the existence of the target object in each grid. After the grid map is obtained, it can be pre-stored in the monitoring center to facilitate the map call when the monitoring center executes the target location pre-storage method provided by the embodiment of the present invention.

[0054] The following describes the process of predicting the position of the target object based on the above steps S100 to S500:

[0055] When the monitoring center receives the ambient sound signal sent by the above-mentioned multiple acoustic positioning sensors, the monitoring center will execute step S100 to extract the target sound signal generated by the target object from the ambient sound signal. The extraction principle is mainly based on the fact that the characteristics of the target sound signal generated by the target object are different from the characteristics of the general ambient noise. For example, taking the target object as a reconnaissance drone as an example, the target sound signal generated by the reconnaissance drone may include at least one of the following: a noise signal generated by propeller rotation, a cyclic noise signal generated by engine operation, a high-frequency noise signal generated by brushless motor operation, etc. The frequencies or other characteristics of these noise signals are obviously different from the general ambient noise. Therefore, the target sound signal generated by the reconnaissance drone can be used to extract the target sound signal from the ambient sound signal containing the target sound signal and the general ambient noise through the specific characteristics of the target sound signal generated by the reconnaissance drone. For the specific extraction principle, please refer to the relevant technology.

[0056] After extracting the target sound signal received by each acoustic positioning sensor, step S200 can be performed to calculate the difference frequency signal for the target sound signals of every two sensors in the above-mentioned multiple acoustic positioning sensors. The calculation principle of the difference frequency signal can be referred to in the relevant technology. It can be seen that one difference frequency signal can be obtained for every two target sound signals. When there are three or more target sound signals, more than one difference frequency signal will be obtained.

[0057] After obtaining multiple difference frequency signals through step S200, the difference frequency signals, the grid map and the position information of multiple acoustic positioning sensors in the grid map can be used to predict the probability of the existence of the target object in each grid. Therefore, before making a prediction, it is necessary to obtain the grid map of the target area. That is, it is necessary to execute step S300 first.

[0058] After obtaining multiple difference frequency signals in step S200 and obtaining a grid map of the target area in step S300, step S400 may be performed to estimate the probability of the target object existing in each grid in the grid map, and update the grid map using the estimated probability, so that the updated grid map records the probability of the target object existing in each grid. In this regard, an embodiment of the present invention proposes a technical solution for estimating the probability of the target object existing in each grid, that is, in the above step S400, the step of determining the probability of the target object existing in each grid in the grid map according to all difference frequency signals may include:

[0059] In step S410, for each grid, a velocity equation corresponding to different difference frequency signals of the grid is constructed based on the position information of the grid, the position information of two acoustic positioning sensors corresponding to each difference frequency signal, and each difference frequency signal;

[0060] In step S420, for each grid, a least square solution is calculated for all speed equations corresponding to the grid to obtain a target speed value with a minimum error and an error of the target speed value;

[0061] In step S430, for each grid, the probability that the target object exists in the grid is determined according to the error of the target speed value corresponding to the grid.

[0062] For step S410, the location information of each grid can be obtained from the grid map. For example, the location of the grid can be represented by the location of the center point of the grid. That is, for each grid, its location information is the location information of its center point. Of course, in other embodiments, in addition to the center point, the location information of any point in the grid can also be taken as the location information of the grid. In order to more accurately express the location of the grid in the embodiment of the present invention, the location information of the center point of the grid is used as the location information of the grid. Similarly, the location information of each acoustic positioning sensor can also be obtained from the grid map. The construction principle of the velocity equation of step S410 is explained below with an example:

[0063] Assume that there are N grids in the grid map, and there are n difference frequency signals calculated in step S200, which are a1~a n; When using the difference frequency signal a1 to construct the corresponding velocity equation for a certain grid A, the Doppler effect and triangulation positioning measurement technology can be used to construct the velocity equation of the target object moving in the grid based on the difference frequency signal a1, the position information of the grid A, and the position information of the two acoustic sensors corresponding to the difference frequency signal a1, which is referred to as the velocity equation corresponding to the grid A. Then, based on the same principle, the velocity equation corresponding to the grid A is continuously constructed using the difference frequency signal a2, and all the difference frequency signals are traversed in this way until the velocity equations corresponding to the grid A are constructed using n difference frequency signals. It can be seen that after completing the execution of step S410, for each grid, a number of velocity equations consistent with the total number of difference frequency signals will be obtained.

[0064] After obtaining multiple sets of speed equations corresponding to each grid through step S410, step S420 can be executed to use the least squares method to solve the least squares solution of the multiple sets of speed equations corresponding to each grid, thereby solving the target speed value with the minimum error and the error of the target speed value.

[0065] After the error of the target speed value corresponding to each grid is obtained by solving the step S420, the step S430 can be executed to determine the probability of the existence of the target object in each grid according to the error corresponding to each grid. In this regard, the embodiment of the present invention proposes a conversion scheme based on error to obtain probability, that is, in some embodiments, in the above step S430, the step of determining the probability of the existence of the target object in the grid according to the error of the target speed value corresponding to the grid may include:

[0066] In step S431, the target error range to which the error of the target speed value corresponding to the grid belongs is determined from a pre-stored mapping relationship; the mapping relationship stores the probabilities corresponding to different error ranges;

[0067] In step S432, a target probability corresponding to the target error range is determined from the mapping relationship, and the target probability is used as the probability that the target object exists in the grid.

[0068] The error range, probability, and the corresponding relationship between the error range and probability in the above mapping relationship can be configured according to actual needs or experience or experiments, and the embodiment of the present invention does not limit this.

[0069] After obtaining the speed and probability corresponding to each grid, the information of each grid in the grid map can be updated. For example, the speed and probability corresponding to each grid can be marked in the corresponding grid in the grid map, or the position information, speed, probability and other information of each grid can be recorded in the form of a matrix. In this way, an updated grid map can be obtained.

[0070] After obtaining the updated grid map, step S500 may be executed to determine the location of the target object according to the information recorded in the updated grid map. In this regard, the embodiment of the present invention provides a solution for determining the location of the target object based on probability, that is, in the above step S500, the step of determining the location of the target object according to the updated grid map may include:

[0071] In step S510, a target grid whose probability is greater than a set probability threshold in the updated grid map is obtained;

[0072] In step S520, the location of the target grid is used as the location of the target object.

[0073] In the above, the probability threshold may be set according to actual needs, experience or experiments, and the embodiment of the present invention does not limit this. For example, in order to obtain a target position with a higher confidence level, the probability threshold may be set to 90% or above.

[0074] Therefore, through step S510 and step S520, the location of the target object can be known, that is, the location of the target grid. It should be understood that when there are multiple target grids, it means that there may be multiple target objects. For example, when there are multiple target grids but they are discretely distributed in the grid map, it means that there may be target objects at different positions in the target area, that is, there may be multiple target objects at this time, and the number of target objects may be the same as the number of target grids; for example, when there are multiple target grids but they are concentrated in a certain place in the grid map, if the size of these multiple target grids is smaller than the size of the target object, it means that there may be only one target object in the target area. If the size of these multiple target grids is larger than the size of the target object, it means that there may be clustered targets in the target area.

[0075] From the above, it can be seen that not only can the location of the target object be predicted based on the updated grid map, but also the number and distribution of the target objects appearing in the target area can be estimated based on the grid map.

[0076] In addition, in order to enable the relevant personnel responsible for controlling the safety of the target area to understand the safety situation of the target area in a timely manner, in some embodiments, the embodiments of the present invention further provide a solution for synchronizing the updated grid map to the relevant personnel, that is, after obtaining the updated grid map, the target object position prediction method provided by the embodiment of the present invention may also include:

[0077] In step S600, the updated grid map is sent to the user terminal bound to the monitoring center.

[0078] A better target position prediction result can be obtained by the target position prediction method in any of the above embodiments. However, in the actual scenario of data transmission, the data sent by different acoustic positioning sensors to the monitoring center may be out of sync due to network delay, large bandwidth load, or wire problems, resulting in inconsistent timing between the ambient sound signals of different acoustic positioning sensors received by the monitoring center, which will affect the prediction accuracy of the target position. Therefore, in order to solve this technical problem, in some embodiments, the embodiments of the present invention also provide a solution to the data delay problem, that is, before step S200, that is, before the step of calculating the difference frequency signal of each two target sound signals, the target position prediction method provided by the embodiments of the present invention may also include:

[0079] In step S20, for every two acoustic positioning sensors, time alignment processing is performed on the environmental sound signals of the two acoustic positioning sensors according to the synchronous sound signals of the two acoustic positioning sensors to obtain two target sound signals with consistent time sequences.

[0080] Correspondingly, in the step of calculating the difference frequency signal between every two target sound signals, every two target sound signals are two target sound signals with the same time sequence.

[0081] Thus, by using the broadcast center to send out synchronous sound signals, the synchronous sound signals received by all acoustic positioning sensors have the same signal characteristics. Therefore, each acoustic positioning sensor sends the synchronous sound signal and the ambient sound signal received at the same time to the monitoring center. For every two acoustic positioning sensors, the monitoring center can use its synchronous sound signal to calculate the time delay between the two, and then use the time delay to correct the timing of the ambient sound signal of one of the acoustic positioning sensors, thereby making the timing of the ambient sound signals sent by the two acoustic positioning sensors consistent. Based on this, if every two acoustic positioning sensors are a group, and the corresponding two target sound signals are a group, then when there are 3 or more acoustic positioning sensors, more than one group of target sound signals can be obtained. After adjusting every two target sound signals to signals with consistent timing through step S20, and then executing step S200, the accuracy of the difference frequency signal calculated based on this can be improved, thereby improving the accuracy of the target position calculated based on the difference frequency signal.

[0082] It is worth noting that the technical features or technical solutions in any of the above embodiments of the present invention can be combined with each other as long as there is no combination contradiction.

[0083] In order to execute the corresponding steps in the above-mentioned target position prediction method embodiment and various possible methods, a method for implementing a target position prediction device is given below. Optionally, the target position prediction device can adopt the above-mentioned Figure 1For further information, please refer to Figure 3 , Figure 3 This is a functional module diagram of a target position prediction device provided by an embodiment of the present invention. It should be noted that the basic principle and technical effects of the target position prediction device provided by this embodiment are the same as those of the above embodiments. For the sake of brief description, for parts not mentioned in this embodiment, reference can be made to the corresponding contents in the above embodiments. The target position prediction device is applied to a monitoring center. The target position prediction device 300 includes:

[0084] The extraction module 310 is configured to: upon receiving the ambient sound signals sent by the plurality of acoustic positioning sensors, extract the target sound signal generated by the target object from the ambient sound signals;

[0085] The calculation module 320 is configured to: calculate and obtain a difference frequency signal between every two target sound signals;

[0086] The acquisition module 330 is configured to: acquire a grid map of the target area;

[0087] The processing module 340 is configured to: determine the probability of the target object existing in each grid in the grid map according to all the difference frequency signals, and update the grid map recording the probability of the target object existing in each grid;

[0088] The determination module 350 is configured to determine the location of the target object according to the updated grid map.

[0089] In some embodiments, the process of the processing module 340 determining the probability of the target object existing in each grid in the grid map according to all the difference frequency signals is configured as follows:

[0090] For each grid, construct a velocity equation corresponding to different difference frequency signals of the grid according to the position information of the grid, the position information of two acoustic positioning sensors corresponding to each difference frequency signal, and each difference frequency signal;

[0091] For each grid, a least square solution is calculated for all speed equations corresponding to the grid to obtain a target speed value with a minimum error and an error of the target speed value;

[0092] For each grid, the probability that the target object exists in the grid is determined according to the error of the target speed value corresponding to the grid.

[0093] In some embodiments, the process of the processing module 340 determining the probability that the target object exists in the grid according to the error of the target speed value corresponding to the grid is configured as follows:

[0094] Determine the target error range to which the error of the target speed value corresponding to the grid belongs from a pre-stored mapping relationship; the mapping relationship stores the probabilities corresponding to different error ranges;

[0095] From the mapping relationship, a target probability corresponding to the target error range is determined, and the target probability is used as a probability that the target object exists in the grid.

[0096] In some embodiments, the process of determining the location of the target object according to the updated grid map by the determination module 350 is configured as follows:

[0097] Obtain the target grid whose probability is greater than the set probability threshold in the updated grid map;

[0098] The position of the target grid is used as the position of the target object.

[0099] In some embodiments, the target position prediction device 300 may further include:

[0100] The timing synchronization module is configured to: before the calculation module 320 calculates the difference frequency signal of each two target sound signals, for each two acoustic positioning sensors, perform time alignment processing on the environmental sound signals of the two acoustic positioning sensors according to the synchronous sound signals of the two acoustic positioning sensors to obtain two target sound signals with consistent timing.

[0101] Accordingly, the calculation module 320 is adjusted and configured to calculate the difference frequency signal of every two target sound signals with consistent time sequences.

[0102] In some embodiments, the target position prediction device 300 may further include:

[0103] The sending module is configured to send the updated grid map to the user terminal bound to the monitoring center.

[0104] Optionally, the above modules can be stored in the form of software or firmware. Figure 1 The memory shown in the figure or solidified in the operating system (OS) of the electronic device, and can be Figure 1 Meanwhile, the data and program codes required for executing the above modules can be stored in the memory.

[0105] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0106] In addition, the functional modules in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0107] If the functions are implemented in the form of software function 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 the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0108] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for predicting the position of a target object, characterized in that: The method is applied to a monitoring center, wherein the monitoring center is used to communicate with a plurality of acoustic positioning sensors arranged at different positions in a target area; the plurality of acoustic positioning sensors are used to simultaneously receive ambient sound signals in the target area, and the monitoring range of the plurality of acoustic positioning sensors covers the target area; the method comprises: When receiving the ambient sound signals sent by the plurality of acoustic positioning sensors, extracting the target sound signal generated by the target object from the ambient sound signals; Calculate and obtain the difference frequency signal between every two target sound signals; Obtaining a grid map of the target area; Determine the probability of the target object existing in each grid in the grid map according to all the difference frequency signals, and update the grid map recording the probability of the target object existing in each grid; The position of the target object is determined according to the updated grid map.

2. The method according to claim 1, characterized in that: The step of determining the probability of the target object existing in each grid in the grid map according to all the difference frequency signals comprises: For each grid, construct a velocity equation corresponding to different difference frequency signals of the grid according to the position information of the grid, the position information of two acoustic positioning sensors corresponding to each difference frequency signal, and each difference frequency signal; For each grid, a least square solution is calculated for all speed equations corresponding to the grid to obtain a target speed value with a minimum error and an error of the target speed value; For each grid, the probability that the target object exists in the grid is determined according to the error of the target speed value corresponding to the grid.

3. The method according to claim 2, characterized in that The step of determining the probability that the target object exists in the grid according to the error of the target speed value corresponding to the grid comprises: Determine the target error range to which the error of the target speed value corresponding to the grid belongs from a pre-stored mapping relationship; the mapping relationship stores the probabilities corresponding to different error ranges; From the mapping relationship, a target probability corresponding to the target error range is determined, and the target probability is used as a probability that the target object exists in the grid.

4. The method according to claim 1, characterized in that: The step of determining the position of the target object according to the updated grid map comprises: Obtain the target grid whose probability is greater than the set probability threshold in the updated grid map; The position of the target grid is used as the position of the target object.

5. The method according to claim 1, characterized in that A broadcast center is also arranged in the target area, and the broadcast center is used to broadcast a synchronous acoustic signal to the multiple acoustic positioning sensors; the multiple acoustic positioning sensors are also used to receive the synchronous acoustic signal while receiving the ambient acoustic signal, and send the synchronous acoustic signal and the ambient acoustic signal received simultaneously to the monitoring center; Before the step of calculating the difference frequency signal between every two target sound signals, the method further includes: For every two acoustic positioning sensors, time alignment processing is performed on the environmental sound signals of the two acoustic positioning sensors according to the synchronous sound signals of the two acoustic positioning sensors to obtain two target sound signals with consistent time sequences; Correspondingly, in the step of calculating the difference frequency signal between every two target sound signals, the every two target sound signals are every two target sound signals with the same time sequence.

6. The method according to any one of claims 1 to 5, characterized in that: After obtaining the updated grid map, the method further includes: The updated grid map is sent to the user terminal bound to the monitoring center.

7. A target position prediction device, characterized in that: Applied to a monitoring center, the monitoring center is used to communicate with a plurality of acoustic positioning sensors arranged at different positions in a target area; the plurality of acoustic positioning sensors are used to simultaneously receive ambient sound signals in the target area, and the monitoring range of the plurality of acoustic positioning sensors covers the target area; the device comprises: The extraction module is configured to: extract the target sound signal generated by the target object from the ambient sound signal when receiving the ambient sound signal sent by the plurality of acoustic positioning sensors; The calculation module is configured to: calculate and obtain a difference frequency signal between every two target sound signals; An acquisition module is configured to: acquire a grid map of the target area; A processing module is configured to: determine the probability of the target object existing in each grid in the grid map according to all the difference frequency signals, and update the grid map recording the probability of the target object existing in each grid; The determination module is configured to: determine the position of the target object according to the updated grid map.

8. A target position prediction system, characterized in that: include: Broadcast center, used to broadcast synchronous sound signals; A plurality of acoustic positioning sensors are arranged at different positions in the target area and are used to simultaneously receive the synchronous sound signal broadcast by the broadcast center and the ambient sound signal in the target area, and the monitoring range of the plurality of acoustic positioning sensors covers the target area; and a monitoring center for communicating with the plurality of acoustic positioning sensors and determining the position of a target object in a target area based on the synchronous acoustic signal, or the synchronous acoustic signal and the ambient acoustic signal, by executing the target object position prediction method according to any one of claims 1 to 6.

9. An electronic device, characterized in that: It comprises a processor and a memory, wherein the memory stores machine executable instructions that can be executed by the processor, and the processor can execute the machine executable instructions to implement the target position prediction method according to any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the target position prediction method according to any one of claims 1 to 6 is implemented.

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