Object situation awareness method, device and equipment and storage medium

Abstract

The invention discloses an object situation awareness method and device, equipment and a storage medium, and relates to the technical field of situation awareness, and the method comprises the steps: obtaining a to-be-sensed object, to-be-detected data corresponding to the to-be-sensed object, and a data space coordinate system, and carrying out the numeralization processing of the to-be-detected data, so as to obtain each target value corresponding to the to-be-detected data; wherein the to-be-detected data is a data set which is continuous in a time sequence; constructing target matrix data according to each target numerical value and the data space coordinate system, and performing parallel calculation on the to-be-detected data according to each target matrix data to obtain a corresponding calculation result; and analyzing a data change condition corresponding to the to-be-detected data on a time sequence according to each calculation result, and obtaining an object situation corresponding to the to-be-detected data according to the data change condition. The to-be-perceived data is mapped into the matrix data, and the matrix data is utilized to carry out situation perception analysis, so that the data processing amount is greatly reduced, and the operation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of situation awareness, and in particular to an object situation awareness method, device, equipment and storage medium. Background Art

[0002] Situation awareness refers to the ability to perceive its surroundings, including the perception of the environment, such as the position, shape, movement, etc. of objects, as well as the perception of its own state. It helps researchers understand or predict the specific state of objects. Situation awareness technology currently has broad application prospects.

[0003] In today's target object situation awareness technology, it mainly relies on direct analysis and processing of image data. However, due to its own characteristics, image data is usually large in size and quite cumbersome to process. This not only leads to low computing efficiency, but also makes the processing cycle lengthy and difficult to meet real-time requirements. Therefore, how to improve the efficiency of object situation awareness has become a technical problem to be solved. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a method, device, equipment and storage medium for object situation awareness, which can map the data to be detected corresponding to the object to be perceived into matrix data, and use the matrix data to analyze and calculate the data to be detected, thereby improving the computational efficiency of situation awareness. The specific scheme is as follows:

[0005] In a first aspect, the present application provides a method for object situation awareness, comprising:

[0006] Determine a target object to be sensed, obtain target data to be detected corresponding to the target object to be sensed, and determine a data space coordinate system corresponding to the target data to be detected;

[0007] Numerical processing is performed on the target data to be detected to obtain target values ​​corresponding to the target data to be detected; wherein the target data to be detected is a data set that is continuous in time series;

[0008] Constructing target matrix data corresponding to the target data to be detected according to the target values ​​and the data space coordinate system, and performing parallel calculation on the target data to be detected according to the target matrix data to obtain corresponding calculation results;

[0009] According to each of the calculation results, the data changes corresponding to the target data to be detected are analyzed in time series, and the object situation corresponding to the target object to be perceived is obtained according to the data changes.

[0010] Optionally, determining a data space coordinate system corresponding to the target data to be detected includes:

[0011] The target data type corresponding to the target data to be detected is determined, and the data space coordinate system having the same latitude as the target data to be detected is determined according to the target data type.

[0012] Optionally, the performing numerical processing on the target data to be detected to obtain target values ​​corresponding to the target data to be detected includes:

[0013] The target data to be detected is numerically processed according to the target data type corresponding to the target data to be detected, so as to obtain each target value corresponding to the target data to be detected.

[0014] Optionally, the performing numerical processing on the target data to be detected according to the target data type corresponding to the target data to be detected includes:

[0015] If the target data type corresponding to the target data to be detected is image data, grayscale processing is performed on the pixels in the target data to be detected, and each grayscale value corresponding to the pixel in the target data to be detected is obtained.

[0016] Optionally, the performing numerical processing on the target data to be detected according to the target data type corresponding to the target data to be detected includes:

[0017] If the target data type corresponding to the target data to be detected is three-dimensional point cloud data, each point cloud data corresponding to the target data to be detected is converted into an integer value.

[0018] Optionally, the object situation awareness method further includes:

[0019] Binarization is performed on each of the target values ​​corresponding to the target data to be detected, and a binary matrix corresponding to the target data to be detected is constructed according to the corresponding processing results and the data space coordinate system, so as to obtain the object posture corresponding to the target data to be detected based on the binary matrix.

[0020] Optionally, the object situation awareness method further includes:

[0021] The data resolution requirement corresponding to each target matrix data is obtained. If the target data resolution corresponding to the data resolution requirement is smaller than the resolution of the target data to be detected, each target matrix data is compressed in equal proportion.

[0022] In a second aspect, the present application provides an object situation awareness device, comprising:

[0023] A coordinate system determination module is used to determine a target object to be sensed, obtain target data to be detected corresponding to the target object to be sensed, and determine a data space coordinate system corresponding to the target data to be detected;

[0024] A numerical value acquisition module, used for performing numerical processing on the target data to be detected to obtain target values ​​corresponding to the target data to be detected; wherein the target data to be detected is a data set that is continuous in time series;

[0025] A data calculation module, used for constructing each target matrix data corresponding to the target data to be detected according to each target value and the data space coordinate system, and performing parallel calculation on the target data to be detected according to each target matrix data to obtain corresponding calculation results;

[0026] The situation awareness module is used to analyze the data changes corresponding to the target data to be detected in a time series according to each of the calculation results, and obtain the object situation corresponding to the target object to be perceived according to the data changes.

[0027] In a third aspect, the present application provides an electronic device, including:

[0028] Memory, used to store computer programs;

[0029] A processor is used to execute the computer program to implement the aforementioned object situation awareness method.

[0030] In a fourth aspect, the present application provides a computer-readable storage medium for storing a computer program, which implements the aforementioned object situation awareness method when executed by a processor.

[0031] The present application first determines the target object to be sensed, obtains the target data to be detected corresponding to the target object to be sensed, and determines the data space coordinate system corresponding to the target data to be detected, and then performs numerical processing on the target data to be detected to obtain each target value corresponding to the target data to be detected; wherein the target data to be detected is a continuous data set in time series, and then constructs each target matrix data corresponding to the target data to be detected according to each target value and the data space coordinate system, and performs parallel calculation on the target data to be detected according to each target matrix data to obtain the corresponding calculation result, and finally analyzes the data change corresponding to the target data to be detected in time series according to each calculation result, and obtains the object situation corresponding to the target object to be sensed according to the data change. It can be seen that the present application avoids directly calculating the data to be detected by mapping the data to be detected corresponding to the object to be sensed into matrix data, and using the matrix data to analyze and calculate the data to be detected, because the amount of matrix data is much smaller than image data, point cloud data or other types of original data to be detected, so the method of using matrix data to analyze and calculate the data to be detected greatly reduces the amount of data processing and improves the operation efficiency of the object situation perception process. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0033] Figure 1 A flow chart of an object situation awareness method provided by this application;

[0034] Figure 2 A specific object situation awareness method flow chart provided for this application;

[0035] Figure 3 A schematic diagram of the structure of an object situation awareness device provided in this application;

[0036] Figure 4 A structural diagram of an electronic device provided for this application. DETAILED DESCRIPTION

[0037] The following will be combined with the 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. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] At present, the method for object situation awareness mainly relies on direct analysis and processing of image data, which has the problem of low computational efficiency. To this end, the present application provides an object situation awareness method, which improves the efficiency of object situation awareness by mapping the data to be detected corresponding to the object to be perceived into matrix data and using the matrix data to analyze and calculate the data to be detected.

[0039] See also Figure 1 As shown, an embodiment of the present invention discloses a method for object situation awareness, including:

[0040] Step S11, determine the target object to be perceived, obtain the target data to be detected corresponding to the target object to be perceived, and determine the data space coordinate system corresponding to the target data to be detected.

[0041] In this embodiment, the morphological data of the target at a certain moment is identified and analyzed in the form of an image, and the deformation state of the target in a certain time period in the future is analyzed and predicted by comparing long-term and large amounts of related morphological data, so as to predict and process the relevant content. It should be noted that the target data to be detected in this embodiment is a continuous data set in a time series, for example, it can be a series of continuous images or video frames. The above process of determining the data space corresponding to the target data to be detected can specifically include: determining the target data type corresponding to the target data to be detected, and determining a data space coordinate system with the same latitude as the target data to be detected according to the target data type; for example, if the data type corresponding to the target data to be detected is image data, then a two-dimensional data space coordinate system with the same latitude as the image data is selected; if the data type corresponding to the target data to be detected is three-dimensional point cloud data, then a three-dimensional data space coordinate system corresponding to the three-dimensional point cloud data is selected. By selecting the data space coordinate system according to the data type of the data to be detected, the reliability of digitizing the data to be detected is guaranteed.

[0042] Step S12, numerically processing the target data to be detected to obtain target values ​​corresponding to the target data to be detected; wherein the target data to be detected is a data set that is continuous in time series.

[0043] In this embodiment, the process of numerically processing the target data to be detected may specifically include: numerically processing the target data to be detected according to the target data type corresponding to the target data to be detected, so as to obtain target numerical values ​​corresponding to the target data to be detected; in a specific implementation, if the target data type corresponding to the target data to be detected is image data, grayscale processing is performed on the pixels in the target data to be detected, and grayscale values ​​corresponding to the pixels in the target data to be detected are obtained; that is, the target data to be detected whose data type is image data is loaded into the corresponding two-dimensional data space, and grayscale processing is performed on it, and the grayscale value corresponding to each pixel is calculated.

[0044] In another specific implementation, if the target data type corresponding to the target data to be detected is three-dimensional point cloud data, each point cloud data corresponding to the target data to be detected is converted into an integer value, that is, the value of the data corresponding to each point in the three-dimensional point cloud data is converted into an integer value; specifically, the three-dimensional point cloud data is loaded into a corresponding three-dimensional data space coordinate system, the three-dimensional point coordinates (x, y, z) of each point in the three-dimensional point cloud data in the coordinate system are obtained, and the data value corresponding to each point is converted into an integer.

[0045] It should be noted that, in the present embodiment, after the matrix data is generated, the data resolution requirement corresponding to each target matrix data can be obtained. If the target data resolution corresponding to the data resolution requirement is smaller than the resolution of the target data to be detected, each target matrix data is proportionally compressed. For example, if the target data to be detected is a series of image data with a size of 90×90 pixels, the size of the generated matrix data is also 90×90. If the target data resolution corresponding to the data resolution requirement is smaller than the resolution of the target data to be detected, the binary matrix data space can be shrunk. The actual storage space of the data can be reduced by reducing the data pixels and tiny edge features. Under the premise that the accuracy permits, it can be compressed into a proportional matrix such as 9*9 or 3*3. In addition, in this embodiment, the unit of digitization can be customized. If the digitization accuracy corresponding to the target data to be detected is allowed to be lower than the accuracy of the target data to be detected itself, the target data to be detected can be divided into modules before generating the target matrix, and digitized in modules; for example, if the target data to be detected is a series of image data with a size of 1600×900 pixels, each image is divided into proportional areas, for example, it is divided into several 40×30 blocks, and digitized in blocks. By digitizing the target data to be detected, the obtained matrix data can be used for physical state perception analysis, which reduces the amount of calculation and improves the calculation efficiency; by performing digitization operations in modules, the amount of calculation in the digitization process is reduced, the calculation efficiency of the digitization process is improved, and the efficiency of object situation perception is thereby improved.

[0046] Step S13, constructing target matrix data corresponding to the target data to be detected according to the target values ​​and the data space coordinate system, and performing parallel calculation on the target data to be detected according to the target matrix data to obtain corresponding calculation results.

[0047] In this embodiment, after the target data to be detected is digitized, the obtained values ​​need to be loaded into the corresponding data space, for example: the horizontal coordinate of the image is used as the x-axis, the vertical coordinate is used as the y-axis, and the gray value is used as the coordinate value to load into the two-dimensional data space coordinate system; and the integer value corresponding to the three-dimensional point cloud data is loaded into the three-dimensional data space coordinate system according to the corresponding three-dimensional coordinates to obtain the matrix data of each target corresponding to the target data to be detected. By obtaining the matrix data corresponding to the target data to be detected and using the matrix data for object situation awareness, the operation of directly using the data to be detected for situation awareness calculation is avoided, the amount of calculation is greatly reduced, and the efficiency of the object situation awareness calculation is improved.

[0048] Step S14: analyzing the data changes corresponding to the target data to be detected in a time series according to the calculation results, and obtaining the object status corresponding to the target object to be sensed according to the data changes.

[0049] In this embodiment, each target to-be-detected data in the time series, such as the data corresponding to the image data, is different. By analyzing the data changes in the time series, the state of the object can be predicted.

[0050] It can be seen that the present application avoids direct calculation of the data to be detected by mapping the data to be detected corresponding to the object to be perceived into matrix data and using the matrix data to analyze and calculate the data to be detected. Since the amount of matrix data is much smaller than image data, point cloud data or other types of original data to be detected, the method of using matrix data to analyze and calculate the data to be detected greatly reduces the amount of data processing and improves the computational efficiency of the object situation perception process.

[0051] Based on the above embodiments, it can be seen that the present application describes the process of numerically processing the data to be detected and performing object situation awareness based on the acquired matrix data. Next, the present application will explain the process of object situation awareness in a specific application scenario. Figure 2 As shown, an embodiment of the present invention discloses a process of object situation awareness, including:

[0052] Step S21, determine the target object to be perceived, obtain the target data to be detected corresponding to the target object to be perceived, determine the data space coordinate system corresponding to the target data to be detected, and perform numerical processing on the target data to be detected to obtain each target value corresponding to the target data to be detected; wherein the target data to be detected is a data set that is continuous in time series.

[0053] Step S22, binarize each of the target values, construct each target binary matrix corresponding to the target data to be detected according to the corresponding processing results and the data space coordinate system, and perform parallel calculation on the data to be detected according to each of the target binary matrices to obtain corresponding calculation results.

[0054] In this embodiment, each target value corresponding to the target data to be detected can be binarized, and a binary matrix corresponding to the target data to be detected can be constructed according to the corresponding processing results and the data space coordinate system, so as to obtain the object situation corresponding to the target data to be detected based on the binary matrix; specifically, if only the target data to be detected is of interest, such as a target in the image data, such as the frost level, the pixel value target of this type is set to 1, and the other targets are set to 0, and the image is binarized, then the final data result of the image data loaded into the data space is a binary matrix, that is, in the data space coordinate system, x and y represent the length and width of the image, data 0 identifies the coordinates where the target data is empty, and data 1 identifies the coordinates where the target data exists, and finally outputs the morphological data of the target at the current moment in the form of a binary matrix; the matrix data obtained by the above operation is used to detect and analyze the target, and the corresponding operation results are recorded, and the above method is used to detect and analyze the data in the time series, and the data at each time node is recorded. Using the above method, the different target data to be detected in the time series are calculated in turn, the change process of the data is compared, and the corresponding calculation target is output. Taking the frosting level analysis as an example, through the analysis of the data, we know that when the frosting pixels in the image begin to increase, the rate of increase, as well as the shape and proportion of other pixels are recorded. When the rate of increase of frosting pixels begins to slow down and the relevant area has become relatively fixed, the changes and shapes of other pixels are calculated, that is, the above calculation results; finally, until it is detected that a certain area disappears and is covered by the area represented by the frosting, the frosting rate and the thickness of the frosting at the current moment, that is, the frosting level, can be inferred from the size of the area. By binarizing the data, the storage space of the matrix data can be reduced, saving the system's storage resources.

[0055] Step S23, analyzing the data changes corresponding to the target data to be detected in time series according to each of the calculation results, and obtaining the object status corresponding to the target object to be sensed according to the data changes.

[0056] In this embodiment, the frost level is taken as an example to analyze the data change. When the regional shape represented by the frost level is relatively fixed, it means that the target surface is completely frosted. Afterwards, when the area of ​​this shape gradually expands, it proves that the frost level is rising. By recording this change in area, it can be converted into the corresponding frost thickness and then obtain the frost level. Furthermore, the three-dimensional frost shape matrix obtained by the frost level conversion can be output for subsequent related processing. That is, in the output record of the data space, the two-dimensional image data can be converted into three-dimensional frost level data (adding thickness space attributes), and then it can be imported into other algorithms as a basis for further calculation and budgeting.

[0057] Similarly, the object situation perception method in this embodiment is also applicable to production scenarios such as weather forecasting and geological analysis that require a large amount of historical data as a basis for calculation. Because these data volumes are relatively large, it is difficult to reasonably allocate computing resources for large-span, large-scale and high-precision scenarios using traditional methods. This problem can be solved well by multidimensional data space technology. Different computing resources and data storage can be reasonably allocated based on the granularity of the data. The motion situation of various types of targets can be simulated through a multidimensional coordinate system, thereby converting the analysis of these data from pure mathematical operations and statistical analysis to visual operations that are easier to identify and understand, and ultimately greatly improving the efficiency and accuracy of related analysis work. By adding latitude features to the data, the situation changes of the object can be more accurately grasped, and the applicability of this method is improved by importing the upgraded data into other algorithms for further budgeting.

[0058] Among them, the specific process of the above step S21 can refer to the corresponding content disclosed in the above embodiment, and will not be repeated here.

[0059] It can be seen that the present application avoids direct calculation of the data to be detected by mapping the data to be detected corresponding to the object to be perceived into matrix data and using the matrix data to analyze and calculate the data to be detected. Since the amount of matrix data is much smaller than image data, point cloud data or other types of original data to be detected, the method of using matrix data to analyze and calculate the data to be detected greatly reduces the amount of data processing and improves the computational efficiency of the object situation perception process.

[0060] See also Figure 3 As shown, the embodiment of the present application discloses an object situation awareness device, including:

[0061] A coordinate system determination module 11 is used to determine a target object to be sensed, obtain target data to be detected corresponding to the target object to be sensed, and determine a data space coordinate system corresponding to the target data to be detected;

[0062] The numerical value acquisition module 12 is used to perform numerical processing on the target data to be detected to obtain each target numerical value corresponding to the target data to be detected; wherein the target data to be detected is a data set that is continuous in time series;

[0063] The data calculation module 13 is used to construct each target matrix data corresponding to the target data to be detected according to each target value and the data space coordinate system, and perform parallel calculation on the target data to be detected according to each target matrix data to obtain corresponding calculation results;

[0064] The situation awareness module 14 is used to analyze the data changes corresponding to the target data to be detected in a time series according to each of the calculation results, and obtain the object situation corresponding to the target object to be perceived according to the data changes.

[0065] It can be seen that the present application avoids direct calculation of the data to be detected by mapping the data to be detected corresponding to the object to be perceived into matrix data and using the matrix data to analyze and calculate the data to be detected. Since the amount of matrix data is much smaller than image data, point cloud data or other types of original data to be detected, the method of using matrix data to analyze and calculate the data to be detected greatly reduces the amount of data processing and improves the computational efficiency of the object situation perception process.

[0066] In some specific embodiments, the coordinate system determination module 11 may specifically include:

[0067] A coordinate system determination unit is used to determine a target data type corresponding to the target data to be detected, and determine the data space coordinate system having the same latitude as the target data to be detected according to the target data type.

[0068] In some specific embodiments, the value acquisition module 12 may specifically include:

[0069] The numerical value acquisition submodule is used to perform numerical processing on the target data to be detected according to the target data type corresponding to the target data to be detected, so as to obtain each target numerical value corresponding to the target data to be detected.

[0070] In some specific embodiments, the value acquisition submodule may specifically include:

[0071] The grayscale value acquisition unit is used to perform grayscale processing on pixels in the target data to be detected and acquire each grayscale value corresponding to the pixels in the target data to be detected if the target data type corresponding to the target data to be detected is image data.

[0072] In some specific embodiments, the value acquisition submodule may specifically include:

[0073] The data conversion unit is used to convert each point cloud data corresponding to the target data to be detected into an integer value if the target data type corresponding to the target data to be detected is three-dimensional point cloud data.

[0074] In some specific embodiments, the object situation awareness device further includes:

[0075] The matrix construction module is used to perform binarization processing on each of the target values ​​corresponding to the target data to be detected, and to construct a binary matrix corresponding to the target data to be detected according to the corresponding processing results and the data space coordinate system, so as to obtain the object posture corresponding to the target data to be detected based on the binary matrix.

[0076] In some specific embodiments, the object situation awareness device further includes:

[0077] The matrix compression module is used to obtain the data resolution requirement corresponding to each target matrix data, and if the target data resolution corresponding to the data resolution requirement is smaller than the resolution of the target data to be detected, each target matrix data is proportionally compressed.

[0078] Furthermore, the present application also discloses an electronic device. Figure 4 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content in the diagram cannot be regarded as any limitation on the scope of use of the present application.

[0079] Figure 4 A schematic diagram of the structure of an electronic device 20 provided in an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the object situation awareness method disclosed in any of the aforementioned embodiments. In addition, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0080] In this embodiment, the power supply 23 is used to provide working voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and the external device, and the communication protocol it follows is any communication protocol that can be applied to the technical solution of the present application, and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0081] In addition, the memory 22 as a carrier for storing resources may be a read-only memory, a random access memory, a disk or an optical disk, etc. The resources stored thereon may include an operating system 221, a computer program 222, etc., and the storage method may be temporary storage or permanent storage.

[0082] The operating system 221 is used to manage and control the hardware devices and computer programs 222 on the electronic device 20, and can be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program that can be used to complete the object situation awareness method performed by the electronic device 20 disclosed in any of the aforementioned embodiments, the computer program 222 can further include a computer program that can be used to complete other specific tasks.

[0083] Furthermore, the present application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the object situation awareness method disclosed above is implemented. For the specific steps of the method, reference may be made to the corresponding contents disclosed in the above embodiments, and no further description will be given here.

[0084] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0085] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0086] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0087] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used 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 presence of other identical elements in the process, method, article or device including the elements.

[0088] The technical solution provided by the present application is introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for general technicians in this field, according to the idea of ​​the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for object situation awareness, characterized in that: include: Determine a target object to be sensed, obtain target data to be detected corresponding to the target object to be sensed, and determine a data space coordinate system corresponding to the target data to be detected; Numerical processing is performed on the target data to be detected to obtain target values ​​corresponding to the target data to be detected; wherein the target data to be detected is a data set that is continuous in time series; Constructing target matrix data corresponding to the target data to be detected according to the target values ​​and the data space coordinate system, and performing parallel calculation on the target data to be detected according to the target matrix data to obtain corresponding calculation results; According to each of the calculation results, the data changes corresponding to the target data to be detected are analyzed in time series, and the object situation corresponding to the target object to be perceived is obtained according to the data changes.

2. The object situation awareness method according to claim 1, characterized in that: The step of determining a data space coordinate system corresponding to the target data to be detected includes: The target data type corresponding to the target data to be detected is determined, and the data space coordinate system having the same latitude as the target data to be detected is determined according to the target data type.

3. The object situation awareness method according to claim 2, characterized in that: The numerical processing of the target data to be detected to obtain target values ​​corresponding to the target data to be detected includes: The target data to be detected is numerically processed according to the target data type corresponding to the target data to be detected, so as to obtain each target value corresponding to the target data to be detected.

4. The object situation awareness method according to claim 3, characterized in that: The performing numerical processing on the target data to be detected according to the target data type corresponding to the target data to be detected includes: If the target data type corresponding to the target data to be detected is image data, grayscale processing is performed on the pixels in the target data to be detected, and each grayscale value corresponding to the pixel in the target data to be detected is obtained.

5. The object situation awareness method according to claim 3, characterized in that: The performing numerical processing on the target data to be detected according to the target data type corresponding to the target data to be detected includes: If the target data type corresponding to the target data to be detected is three-dimensional point cloud data, each point cloud data corresponding to the target data to be detected is converted into an integer value.

6. The object situation awareness method according to claim 1, characterized in that: Also includes: Binarization is performed on each of the target values ​​corresponding to the target data to be detected, and a binary matrix corresponding to the target data to be detected is constructed according to the corresponding processing results and the data space coordinate system, so as to obtain the object posture corresponding to the target data to be detected based on the binary matrix.

7. The object situation awareness method according to any one of claims 1 to 6, characterized in that: Also includes: The data resolution requirement corresponding to each target matrix data is obtained. If the target data resolution corresponding to the data resolution requirement is smaller than the resolution of the target data to be detected, each target matrix data is compressed in equal proportion.

8. An object situation awareness device, characterized in that: include: A coordinate system determination module is used to determine a target object to be sensed, obtain target data to be detected corresponding to the target object to be sensed, and determine a data space coordinate system corresponding to the target data to be detected; A numerical value acquisition module, used for performing numerical processing on the target data to be detected to obtain target values ​​corresponding to the target data to be detected; wherein the target data to be detected is a data set that is continuous in time series; A data calculation module, used for constructing each target matrix data corresponding to the target data to be detected according to each target value and the data space coordinate system, and performing parallel calculation on the target data to be detected according to each target matrix data to obtain corresponding calculation results; The situation awareness module is used to analyze the data changes corresponding to the target data to be detected in a time series according to each of the calculation results, and obtain the object situation corresponding to the target object to be perceived according to the data changes.

9. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the object situation awareness method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Used to store a computer program, which, when executed by a processor, implements the object situation awareness method as described in any one of claims 1 to 7.

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