A radar geographic information and echo fusion processing sample selection method and device

Abstract

The present application relates to the technical field of signal processing, and provides a radar geographic information and echo fusion processing sample selection method and device. The present application uses a first echo information evaluation index and a first geographic information evaluation index to perform sample screening on historical data, to obtain a first clutter residue and a second clutter residue; according to the first clutter residue and the second clutter residue, a first fusion weight and a second fusion weight are determined; according to a fusion evaluation index, echo data is arranged from small to large, and the first preset number of echo data is determined as a training sample, thereby solving the problem that the prior art cannot effectively suppress non-uniform clutter when facing a scene in which a strong scatterer on the ground moves.

Description

Technical Field

[0001] This invention relates to the field of signal processing technology, and in particular to a method and apparatus for selecting samples for radar geographic information and echo fusion processing. Background Technology

[0002] Space-Time Adaptive Processing (STAP) plays a crucial role in airborne radar clutter suppression. The core of this technique lies in constructing the clutter covariance matrix of the target cell. However, in practice, factors such as terrain undulations, weather changes, and artificial strong scattering points cause non-uniform clutter distribution, resulting in a smaller number of training samples satisfying the Independent and Identically Distributed (IID) condition. This leads to biases in the estimation of the clutter covariance matrix, thereby reducing the clutter suppression performance of STAP.

[0003] In existing technologies, some schemes achieve non-uniform clutter suppression through sparse recovery, estimating the covariance matrix from a small number of uniform samples. Other schemes employ non-uniform detection to suppress non-uniform clutter, eliminating outliers by analyzing training samples. However, these existing schemes only consider geographical information or the interrelationships between signals, making their algorithm performance highly susceptible to clutter distribution. In scenarios with moving, strong scattering objects on the ground, algorithm performance degrades, resulting in poor non-uniform clutter suppression and limited practicality in complex scenarios. This leads to an insufficient number of training samples satisfying the independent and identically distributed condition, failing to meet the practical application requirements for constructing the clutter covariance matrix of the target unit.

[0004] Therefore, overcoming the shortcomings of the existing technology is an urgent problem to be solved in this technical field. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method and apparatus for selecting radar geographic information and echo fusion processing samples. The purpose is to provide a radar sample selection scheme based on the fusion processing of geographic information and echo information, which selects echo data with smaller fusion evaluation index as training samples. It has high practicality in complex scenarios and solves the problem that the existing technology only considers the relationship between geographic information or signals, and the corresponding algorithm performance is greatly affected by clutter distribution. In the case of scenarios with moving strong scatterers on the ground, the effect of non-uniform clutter suppression is poor.

[0006] The present invention adopts the following technical solution:

[0007] In a first aspect, the present invention provides a method for selecting samples for radar geographic information and echo fusion processing, comprising:

[0008] The first echo information evaluation index is used to filter the historical data to obtain the first clutter residue; the first geographic information evaluation index is used to filter the historical data to obtain the second clutter residue.

[0009] The first fusion weight and the second fusion weight are determined based on the first clutter residue and the second clutter residue;

[0010] Determine the second echo information evaluation index and the second geographic information evaluation index for the echo data; wherein the echo data and the historical data are at the same wave position;

[0011] Based on the second echo information evaluation index and the first fusion weight, as well as the second geographic information evaluation index and the second fusion weight, a fusion evaluation index is obtained; the echo data are arranged from smallest to largest according to the fusion evaluation index, and the first preset number of echo data are determined as training samples.

[0012] Furthermore, before using the first geographic information evaluation index to filter the historical data to obtain the second clutter residue, the method further includes:

[0013] According to the coordinate position of the carrier aircraft, the clutter block on each range ring is divided into multiple information points; the ground grazing angle of each information point relative to the carrier aircraft is determined; the ground cover data and the ground grazing angle are input into the airborne radar clutter model to obtain the backscattering coefficient of each information point; the information points are used as historical data, and a priori knowledge database is constructed using the historical data and the corresponding backscattering coefficients.

[0014] Determine the normalized Doppler frequency of each information point on the distance ring, and divide the normalized Doppler frequency into multiple Doppler intervals;

[0015] The geographical environment is divided into region A and region B, with the flight direction of the carrier aircraft as the boundary; the weight of the first information point in each Doppler interval in region A is determined, and the weight of the second information point in each Doppler interval in region B is determined.

[0016] Based on the prior knowledge database, a weighted vector for region A is constructed using the weights of the first information points, and a weighted vector for region B is constructed using the weights of the second information points; the first geographic information evaluation index is determined based on the weighted vectors for region A and region B.

[0017] Further, determining the first information point weights for each Doppler interval in region A and the second information point weights for each Doppler interval in region B includes:

[0018] In region A, information points located at the same distance gate and in the same Doppler interval are grouped into the same information point set to obtain at least one information point set in region A; in region B, information points located at the same distance gate and in the same Doppler interval are grouped into the same information point set to obtain at least one information point set in region B.

[0019] For each set of information points in region A, calculate the azimuth angle between each information point and the corresponding airborne radar array, and calculate the first mean of the azimuth angles of all information points in the set of information points in region A; for each set of information points in region B, calculate the azimuth angle between each information point and the corresponding airborne radar array, and calculate the second mean of the azimuth angles of all information points in the set of information points in region B.

[0020] Based on the relationship between the first mean and the corresponding second mean, the first information point weight of the corresponding A region information point set and the second information point weight of the corresponding B region information point set are determined to obtain the first information point weight of all A region information point sets and the second information point weight of all B region information point sets; wherein, the information points corresponding to the first mean and the corresponding second mean are located in the same Doppler interval.

[0021] Further, determining the first information point weight of the corresponding A region information point set and the second information point weight of the corresponding B region information point set based on the relationship between the first mean and the corresponding second mean includes:

[0022] When the first mean is equal to the corresponding second mean, the weight of the first information point is set to one; the weight of the second information point is set to one.

[0023] When the first mean is not equal to the corresponding second mean, the sum of the first mean and the corresponding second mean is determined as the median value; the ratio of the corresponding second mean to the median value is determined as the weight of the first information point; and the ratio of the corresponding first mean to the median value is determined as the weight of the second information point.

[0024] Further, based on the prior knowledge database, a weighted vector for region A is constructed using the weights of the first information points, and a weighted vector for region B is constructed using the weights of the second information points; the first geographic information evaluation index is determined based on the weighted vectors for region A and region B, including:

[0025] Based on the backscattering coefficients of historical data of various landform types in the prior knowledge database, the information point set of region A is represented by normalized vectors of various landform types to obtain the normalized vector of region A; the information point set of region B is represented by normalized vectors of various landform types to obtain the normalized vector of region B.

[0026] Using the backscattering coefficients of the corresponding information points and the weights of the first information points in the A region information point set, the normalized vector of the A region is weighted to obtain the A region weighted vector; using the backscattering coefficients of the corresponding information points and the weights of the second information points, the normalized vector of the B region information point set is weighted to obtain the B region weighted vector.

[0027] Determine the mean of the weighted vector of region A; calculate the first distance between the weighted vector of region A and the mean of region A; determine the mean of the weighted vector of region B; calculate the second distance between the weighted vector of region B and the mean of region B; and determine the sum of the first distance and the second distance as the first geographic information evaluation index.

[0028] Furthermore, the expression for the normalized Doppler frequency is:

[0029]

[0030] in, For the flight speed of the carrier aircraft, For wavelength, The pulse repetition frequency, For the first In the distance ring, the first The angle between each information point and the array axis. The angle between the array axis and the carrier direction is denoted by . For the first The pitch angle of each information point on the distance ring;

[0031] The expression for the range of the plurality of Doppler intervals is:

[0032]

[0033] in, s k For the range of intervals, This indicates the number of Doppler intervals that have been divided.

[0034] Furthermore, the expression for the first echo information evaluation index is:

[0035]

[0036] in, For the first The echo data vector of each distance gate, It can be represented as the conjugate transpose of a matrix. For the first The space-time dimensionality reduction matrix of each Doppler channel. For use L The inverse matrix of the covariance matrix estimated from the echo data.

[0037] Furthermore, the expression for the fusion evaluation index is as follows:

[0038]

[0039] in, Indicates the integration evaluation indicators, This indicates the evaluation index for the second echo information. This represents the second geographic information evaluation indicator; This represents the maximum value among the evaluation indicators for the second echo information. This represents the maximum value among the second geographic information evaluation indicators; This represents the first fusion weight. This represents the second fusion weight.

[0040] Secondly, the present invention also provides a radar geographic information and echo fusion processing sample selection device, comprising:

[0041] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the processor for performing the radar geographic information and echo fusion processing sample selection method described in the first aspect.

[0042] Thirdly, the present invention also provides a non-volatile computer storage medium storing computer-executable instructions, which are executed by one or more processors to perform the radar geographic information and echo fusion processing sample selection method described in the first aspect.

[0043] Fourthly, a computer program product containing instructions is provided, which, when executed on a computer or processor, causes the computer or processor to perform the radar geographic information and echo fusion processing sample selection method as described in the first aspect.

[0044] Fifthly, the present invention also provides a radar geographic information and echo fusion processing sample selection system, including the radar geographic information and echo fusion processing sample selection device as described in the second aspect, and using the radar geographic information and echo fusion processing sample selection method as described in the first aspect to complete the interaction of the radar geographic information and echo fusion processing sample selection device of the second aspect.

[0045] Unlike existing technologies, the present invention has at least the following beneficial effects:

[0046] This invention uses two evaluation metrics, echo information and geographic information, to screen historical data samples and calculate corresponding fusion weights to construct fusion evaluation metrics. By using multi-dimensional information weighted fusion, the screening dimensions for training samples are expanded to achieve a more suitable training sample set selection. The echo data are arranged from smallest to largest according to the fusion evaluation metrics, and the first preset number of echo data are determined as training samples. The non-uniform clutter suppression effect is better, solving the problem that the existing technology has poor non-uniform clutter suppression effect when facing scenarios with moving strong scatterers on the ground. Attached Figure Description

[0047] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments of the present invention will be briefly described below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0048] Figure 1 This is a flowchart illustrating a method for selecting samples in radar geographic information and echo fusion processing according to an embodiment of the present invention.

[0049] Figure 2 This is a schematic diagram illustrating a specific example of a radar geographic information and echo fusion processing sample selection method provided in an embodiment of the present invention;

[0050] Figure 3 This is a flowchart illustrating step 10 provided in an embodiment of the present invention;

[0051] Figure 4 This is a flowchart illustrating step 103 provided in an embodiment of the present invention;

[0052] Figure 5 This is a flowchart illustrating step 104 provided in an embodiment of the present invention;

[0053] Figure 6 This is a schematic diagram of the architecture of a radar geographic information and echo fusion processing sample selection device provided in an embodiment of the present invention. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0055] Unless the context otherwise requires, throughout the specification and claims, the term "comprising" is interpreted as openly inclusive, meaning "including, but not limited to." In the description of the specification, terms such as "one embodiment," "some embodiments," "exemplary embodiment," "example," "specific example," or "some examples" are intended to indicate that a particular feature, structure, material, or characteristic associated with that embodiment or example is included in at least one embodiment or example of this disclosure. The illustrative representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics mentioned may be included in any suitable manner in any one or more embodiments or examples; that is, although they may be incorporated into embodiments or examples using the above terms for reasons such as order and position, it does not limit them to be incorporated in combination by a single embodiment or example.

[0056] In the description of this invention, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this disclosure and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this disclosure.

[0057] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of embodiments of this disclosure, unless otherwise stated, "a plurality of" means two or more. Furthermore, for example, the description may use the prefix "A" or "B" to describe the same type of nouns as two independent entities. In this case, the corresponding features defined with "A" and "B" are used only to distinguish between similar entities and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features.

[0058] In describing some embodiments, the terms "coupled," "coupled," and "connected," and their derivative expressions, may be used. For example, the term "connected" may be used in describing some embodiments to indicate that two or more components have direct physical or electrical contact with each other. Similarly, the term "coupled" may be used in describing some embodiments to indicate that two or more components have direct physical or electrical contact. However, the terms "connected" or "coupled" may also refer to two or more components that do not have direct contact with each other but still cooperate or interact with each other, such as "optical coupling," "wireless connection," etc. The embodiments disclosed herein are not necessarily limited to the scope of this invention.

[0059] In the description of this invention, the expression “A and / or B” (where A and B are used to formally represent specific features) will be used. The corresponding expression includes the following three combinations: only A, only B, and a combination of A and B.

[0060] As used in this invention, “about,” “approximately,” or “approximately” includes the stated value and the average value within an acceptable range of deviation from a particular value, wherein the acceptable range of deviation is determined by a person skilled in the art taking into account the measurement under discussion and the error associated with the measurement of the particular quantity (i.e., the limitations of the measurement system).

[0061] Furthermore, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0062] Example 1:

[0063] To solve the above problems, such as Figure 1 As shown, this embodiment of the invention provides a method for selecting samples for radar geographic information and echo fusion processing, including:

[0064] Step 10: Use the first echo information evaluation index to filter the historical data to obtain the first clutter residue; use the first geographic information evaluation index to filter the historical data to obtain the second clutter residue.

[0065] The historical data refers to the historical echo data of radar on a specific Doppler channel. The first echo information evaluation index and the first geographic information evaluation index are both sets of corresponding evaluation indicators.

[0066] like Figure 2 As shown, in this embodiment of the invention, historical data is analyzed for a selected Doppler channel, and echo information is used to evaluate the indicators. Geographic information evaluation indicators Sample selection was performed on historical data separately, resulting in training sample sets selected based on two evaluation metrics. Using these two sets of training samples, two sets of covariance matrices were estimated, and the first clutter residual was obtained using spatiotemporal adaptive processing techniques. Second clutter residue .

[0067] In one embodiment, the expression for the first echo information evaluation index is:

[0068]

[0069] in, For the first The echo data vector of each distance gate, It can be represented as the conjugate transpose of a matrix. For the first The space-time dimensionality reduction matrix of each Doppler channel. For use L The covariance matrix estimated from the echo data. For use L The inverse matrix of the covariance matrix estimated from the echo data; the expression for the covariance matrix is:

[0070]

[0071] Step 20: Determine the first fusion weight and the second fusion weight based on the first clutter residue and the second clutter residue.

[0072] In one embodiment, the expressions for the first fusion weight and the second fusion weight are:

[0073]

[0074] in, This represents the first fusion weight. This represents the second fusion weight.

[0075] Step 30: Determine the second echo information evaluation index and the second geographic information evaluation index of the echo data; wherein the echo data and the historical data are at the same wave position.

[0076] like Figure 2 As shown, for echo data that is at the same wave position on the Doppler channel as historical data, two sets of evaluation indicators, namely echo information and geographic information, are calculated respectively.

[0077] Step 40: Obtain the fusion evaluation index based on the second echo information evaluation index and the first fusion weight, as well as the second geographic information evaluation index and the second fusion weight; arrange the echo data from smallest to largest according to the fusion evaluation index, and determine the first preset number of echo data as training samples.

[0078] The preset number is selected by those skilled in the art based on the specific application scenario, and is not limited here; in this embodiment of the invention, echo data with smaller fusion evaluation indicators are used as training samples.

[0079] The second echo information evaluation index and the second geographic information evaluation index are normalized and then weighted and summed to obtain the fused evaluation index. In one embodiment, the expression of the fused evaluation index is:

[0080]

[0081] in, Indicates the integration evaluation indicators, This indicates the evaluation index for the second echo information. This represents the second geographic information evaluation indicator; This represents the maximum value among the evaluation indicators for the second echo information. This represents the maximum value among the second geographic information evaluation indicators; This represents the first fusion weight. This represents the second fusion weight.

[0082] This invention uses two evaluation metrics, echo information and geographic information, to screen historical data samples and calculate corresponding fusion weights to construct fusion evaluation metrics. By using multi-dimensional information weighted fusion, the screening dimensions for training samples are expanded to achieve a more suitable training sample set selection. The echo data are arranged from smallest to largest according to the fusion evaluation metrics, and the first preset number of echo data are determined as training samples. The non-uniform clutter suppression effect is better, solving the problem that the existing technology has poor non-uniform clutter suppression effect when facing scenarios with moving strong scatterers on the ground.

[0083] The first geographic information evaluation index is calculated through the following steps: First, a prior knowledge database is constructed; second, information points are mapped and regions are divided, and then the weights of the information point set are determined; then, a weighted normalized vector is constructed, and finally, samples are selected by calculating the geographic information evaluation index. Specifically, as follows... Figure 3 As shown, before step 10, which involves using the first geographic information evaluation index to filter the historical data and obtain the second clutter remainder, the method further includes:

[0084] Step 101: According to the coordinate position of the carrier aircraft, divide the clutter block on each range ring into multiple information points; determine the ground grazing angle of each information point relative to the carrier aircraft; input the ground cover data and the ground grazing angle into the airborne radar clutter model to obtain the backscattering coefficient of each information point; use the information points as historical data, and use the historical data and the corresponding backscattering coefficients to construct a priori knowledge database.

[0085] In one embodiment, during the construction of the prior knowledge database, firstly, based on the aircraft's coordinates and combined with a 30m digital elevation model, the clutter block on each range ring is divided into multiple information points with an accuracy of 30m; secondly, the ground-scraping angle of each information point relative to the aircraft is calculated; finally, based on the 30m fine ground cover data and combined with the airborne radar clutter model, the backscattering coefficient of each information point is estimated.

[0086] Step 102: Determine the normalized Doppler frequency of each information point on the distance ring, and divide the normalized Doppler frequency into multiple Doppler intervals.

[0087] To save computation, Doppler intervals are divided. However, since clutter is distributed differently at different Doppler frequencies, in real-world scenarios, it is possible that one Doppler interval is affected while another is not, which will affect the final ranking of training samples.

[0088] In one embodiment, the expression for the normalized Doppler frequency is:

[0089]

[0090] in, For the flight speed of the carrier aircraft, For wavelength, The pulse repetition frequency, For the first In the distance ring, the first The angle between each information point and the array axis. The angle between the array axis and the carrier direction is denoted by . For the first The pitch angle of each information point on the distance ring.

[0091] In one embodiment, the expression for the range of the plurality of Doppler intervals is:

[0092]

[0093] in, s k For the range of intervals, This indicates the number of Doppler intervals that have been divided.

[0094] Step 103: Divide the geographical environment into region A and region B using the aircraft's flight direction as the boundary; determine the first information point weight of each information point in each Doppler interval in region A, and determine the second information point weight of each information point in each Doppler interval in region B.

[0095] For airborne radar, regions A and B are independent and therefore need to be calculated separately. Since a certain Doppler interval may exist in both regions A and B, it is necessary to distinguish information points in regions A and B according to the Doppler interval and determine the information point weight of each type of information point.

[0096] In one alternative embodiment, region A is located to the left of the aircraft's flight direction, and region B is located to the right of the aircraft's flight direction.

[0097] Step 104: Based on the prior knowledge database, construct a weighted vector for region A using the weights of the first information points, and construct a weighted vector for region B using the weights of the second information points; determine the first geographic information evaluation index based on the weighted vectors for region A and region B.

[0098] To explain the process of obtaining the weights of the first and second information points, as follows: Figure 4 As shown, in step 103, determining the first information point weights of information points within each Doppler interval in region A and the second information point weights of information points within each Doppler interval in region B includes:

[0099] Step 1031: In region A, information points located at the same distance gate and in the same Doppler interval are grouped into the same information point set to obtain at least one information point set in region A; in region B, information points located at the same distance gate and in the same Doppler interval are grouped into the same information point set to obtain at least one information point set in region B.

[0100] Among them, information points located at the same distance gate and in the same Doppler interval refer to information points located at the same distance gate and whose normalized Doppler frequencies are in the same Doppler interval.

[0101] Step 1032: For each set of information points in region A, calculate the azimuth angle between each information point and the corresponding airborne radar array, and calculate the first mean of the azimuth angles of all information points in the set of information points in region A; for each set of information points in region B, calculate the azimuth angle between each information point and the corresponding airborne radar array, and calculate the second mean of the azimuth angles of all information points in the set of information points in region B.

[0102] Step 1033: Based on the relationship between the first mean and the corresponding second mean, determine the first information point weight of the corresponding A region information point set and the second information point weight of the corresponding B region information point set, so as to obtain the first information point weight of all A region information point sets and the second information point weight of all B region information point sets; wherein, the information points corresponding to the first mean and the corresponding second mean are located in the same Doppler interval.

[0103] Specifically, step 1033 includes:

[0104] When the first mean is equal to the corresponding second mean, the weight of the first information point is set to one; the weight of the second information point is set to one.

[0105] When the first mean is not equal to the corresponding second mean, the sum of the first mean and the corresponding second mean is determined as the median value; the ratio of the corresponding second mean to the median value is determined as the weight of the first information point; and the ratio of the corresponding first mean to the median value is determined as the weight of the second information point.

[0106] In one embodiment, the expression can be:

[0107]

[0108] in, The weight of the first information point. The weight of the second information point. The first mean, The second mean, This is the median value.

[0109] For airborne radar, the signal radiation intensity received by different airborne radar arrays may vary depending on the Doppler interval. Generally, the smaller the pointing angle of the airborne radar array, the higher the intensity of the radiated signal and the greater the impact; conversely, the larger the pointing angle, the lower the intensity of the radiated signal and the less the impact. This invention distinguishes between intervals with high and low radiated signal intensity by dividing the Doppler intervals, facilitating subsequent weighted processing using information point weights to prioritize the intervals with higher radiated signal intensity.

[0110] To illustrate the process of obtaining the weighted vectors for region A and region B, as follows: Figure 5 As shown, step 104 includes:

[0111] Step 1041: Based on the backscattering coefficients of historical data of various landform types in the prior knowledge database, represent the information point set of region A using normalized vectors of various landform types to obtain the normalized vector of region A; represent the information point set of region B using normalized vectors of various landform types to obtain the normalized vector of region B.

[0112] Step 1042: Using the backscattering coefficients of the corresponding information points and the weights of the first information points in the A region information point set, the normalized vector of the A region is weighted to obtain the A region weighted vector; using the backscattering coefficients of the corresponding information points and the weights of the second information points, the normalized vector of the B region information point set is weighted to obtain the B region weighted vector.

[0113] In constructing the corresponding weighted vectors, based on the prior knowledge database, the information point sets of region A and region B can be represented by normalized vectors of landform types consisting of 8 elements, corresponding to the proportions of landform types such as farmland, forest, shrubland / grassland, wetland, artificial structures, water bodies, exposed areas, and glaciers, respectively. The expression is as follows:

[0114]

[0115] in, This represents the weighted vector for region A. This represents the weighted vector for region B. Indicates the first in region A The set of information points in region A, or the first information point in region B. A set of information points in region B; j Indicates the first j Types of landforms.

[0116] Since the backscattering coefficients of different landform types vary, and the proportion of different landform types has different effects on the degree of clutter non-uniformity, in order to better reflect the surface information characteristics, the normalized vector of landform types is weighted using the backscattering coefficient and information point weights. The calculation formula is as follows:

[0117]

[0118] in, This represents the weighted vector for region A. This represents the weighted vector for region B. This represents the number of information points belonging to the j-th landform in the set of information points with the same Doppler frequency and distance gate in region A. This represents the number of information points belonging to the j-th landform in the set of information points with the same Doppler frequency and distance gate in region B. Indicates the number of the information point. This represents the backscattering coefficient of the j-th landform in the information point set of region A. Let represent the backscattering coefficient of the j-th landform in the information point set of region B. This represents the set of information points in region A that have the same Doppler frequency and range gate and belong to the j-th type of terrain. This represents the set of information points in region B that have the same Doppler frequency and distance gate and belong to the j-th type of landform.

[0119] Step 1043: Determine the mean of the weighted vector of region A in region A; calculate the first distance between the weighted vector of region A and the mean of region A; determine the mean of the weighted vector of region B in region B; calculate the second distance between the weighted vector of region B and the mean of region B; and determine the sum of the first distance and the second distance as the first geographic information evaluation index.

[0120] Here, both the first distance and the second distance refer to Euclidean distance.

[0121] In the process of calculating geographic information evaluation indicators, the corresponding expressions for geographic information evaluation indicators for regions A and B are calculated separately in the selected Doppler channel as follows:

[0122]

[0123] in, Represents Euclidean distance. This represents the weighted vector for region A. This represents the weighted vector for region B. The mean of region A, The mean of region B is expressed as follows:

[0124]

[0125] The radar geographic information and echo fusion processing sample selection of the embodiments of the present invention has good robustness in different clutter environments and good training sample selection performance in complex environments containing discrete moving scatterers on the ground.

[0126] Example 2:

[0127] like Figure 6 The diagram shown is an architectural schematic of a radar geographic information and echo fusion processing sample selection device according to an embodiment of the present invention. The radar geographic information and echo fusion processing sample selection device of this embodiment includes one or more processors 21 and a memory 22. Figure 6 Take a processor 21 as an example.

[0128] Processor 21 and memory 22 can be connected via a bus or other means. Figure 6 Taking the example of a connection between China and Israel via a bus.

[0129] The memory 22, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs and non-volatile computer-executable programs, such as the radar geographic information and echo fusion processing sample selection method in this embodiment. The processor 21 executes the radar geographic information and echo fusion processing sample selection method by running the non-volatile software program and instructions stored in the memory 22.

[0130] Memory 22 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, memory 22 may optionally include memory remotely located relative to processor 21, which can be connected to processor 21 via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0131] The program instructions / modules are stored in the memory 22. When executed by one or more processors 21, they execute the radar geographic information and echo fusion processing sample selection method in the above embodiments. For example, they execute each step of the radar geographic information and echo fusion processing sample selection method of the present invention embodiments described above.

[0132] This invention also provides a non-volatile computer storage medium storing computer-executable instructions that are executed by one or more processors, for example... Figure 6 A processor 21 can enable one or more of the processors to execute the radar geographic information and echo fusion processing sample selection method in the specific embodiments of the present invention, for example, to execute each step of the radar geographic information and echo fusion processing sample selection method described above in the embodiments of the present invention; it can also implement Figure 6 The various modules and units described above; or the radar geographic information and echo fusion processing sample selection method in the specific embodiments of the present invention, for example, executing the various steps of the radar geographic information and echo fusion processing sample selection method described above in the embodiments of the present invention; can also be implemented. Figure 6 The various modules and units mentioned above.

[0133] It is worth noting that the information interaction and execution process between the modules and units in the above-mentioned device and system are based on the same concept as the processing method embodiment of the present invention. For details, please refer to the description in the method embodiment of the present invention, and will not be repeated here.

[0134] Those skilled in the art will understand that all or part of the steps in the various methods of the embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk, etc.

[0135] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for selecting samples in radar geographic information and echo fusion processing, characterized in that, include: The first echo information evaluation index is used to filter historical data samples to obtain the first clutter residue; The historical data was sampled using the first geographic information evaluation index to obtain the second clutter residue; The expression for the first echo information evaluation index is as follows: ;in, For the first The echo data vector of each distance gate, It can be represented as the conjugate transpose of a matrix. For the first The space-time dimensionality reduction matrix of each Doppler channel. For use The inverse matrix of the covariance matrix estimated from each echo data; Specifically, based on the aircraft's coordinates, clutter blocks on each range ring are divided into multiple information points; the ground grazing angle of each information point relative to the aircraft is determined; ground cover data and the ground grazing angle are input into an airborne radar clutter model to obtain the backscattering coefficient of each information point; these information points are used as historical data, and a priori knowledge database is constructed using the historical data and the corresponding backscattering coefficients; the normalized Doppler frequency of each information point on each range ring is determined, and the normalized Doppler frequency is divided into multiple Doppler intervals; the geographical environment is divided into region A and region B, with the aircraft's flight direction as the boundary; the first information point weight is determined for each Doppler interval in region A, and the second information point weight is determined for each Doppler interval in region B; based on the prior knowledge database, a weighted vector for region A is constructed using the first information point weight, and a weighted vector for region B is constructed using the second information point weight; the first geographical information evaluation index is determined based on the weighted vectors for regions A and B. The first fusion weight and the second fusion weight are determined based on the first clutter residue and the second clutter residue; Determine the second echo information evaluation index and the second geographic information evaluation index for the echo data; wherein the echo data and the historical data are at the same wave position; Based on the second echo information evaluation index and the first fusion weight, as well as the second geographic information evaluation index and the second fusion weight, a fusion evaluation index is obtained; the echo data are arranged from smallest to largest according to the fusion evaluation index, and the first preset number of echo data are determined as training samples; the expression of the fusion evaluation index is: ; in, Indicates the integration evaluation indicators, This indicates the evaluation index for the second echo information. This represents the second geographic information evaluation indicator; This represents the maximum value among the evaluation indicators for the second echo information. This represents the maximum value among the second geographic information evaluation indicators; This represents the first fusion weight. This represents the second fusion weight.

2. The radar geographic information and echo fusion processing sample selection method according to claim 1, characterized in that, The process of determining the first information point weights for each Doppler interval in region A and the second information point weights for each Doppler interval in region B includes: In region A, information points located at the same distance gate and in the same Doppler interval are grouped into the same information point set to obtain at least one information point set in region A; in region B, information points located at the same distance gate and in the same Doppler interval are grouped into the same information point set to obtain at least one information point set in region B. For each set of information points in region A, calculate the azimuth angle between each information point and the corresponding airborne radar array, and calculate the first mean of the azimuth angles of all information points in the set of information points in region A; for each set of information points in region B, calculate the azimuth angle between each information point and the corresponding airborne radar array, and calculate the second mean of the azimuth angles of all information points in the set of information points in region B. Based on the relationship between the first mean and the corresponding second mean, the first information point weight of the corresponding A region information point set and the second information point weight of the corresponding B region information point set are determined to obtain the first information point weight of all A region information point sets and the second information point weight of all B region information point sets; wherein, the information points corresponding to the first mean and the corresponding second mean are located in the same Doppler interval.

3. The radar geographic information and echo fusion processing sample selection method according to claim 2, characterized in that, The step of determining the first information point weight of the corresponding A region information point set and the second information point weight of the corresponding B region information point set based on the relationship between the first mean and the corresponding second mean includes: When the first mean is equal to the corresponding second mean, the weight of the first information point is set to one; the weight of the second information point is set to one. When the first mean is not equal to the corresponding second mean, the sum of the first mean and the corresponding second mean is determined as the median value; the ratio of the corresponding second mean to the median value is determined as the weight of the first information point; and the ratio of the corresponding first mean to the median value is determined as the weight of the second information point.

4. The radar geographic information and echo fusion processing sample selection method according to claim 2, characterized in that, Based on the prior knowledge database, a weighted vector for region A is constructed using the weights of the first information points, and a weighted vector for region B is constructed using the weights of the second information points. Based on the weighted vector of region A and the weighted vector of region B, the first geographic information evaluation index is determined as follows: Based on the backscattering coefficients of historical data of various landform types in the prior knowledge database, the information point set of region A is represented by normalized vectors of various landform types to obtain the normalized vector of region A; the information point set of region B is represented by normalized vectors of various landform types to obtain the normalized vector of region B. Using the backscattering coefficients of the corresponding information points and the weights of the first information points in the A region information point set, the normalized vector of the A region is weighted to obtain the A region weighted vector; using the backscattering coefficients of the corresponding information points and the weights of the second information points, the normalized vector of the B region information point set is weighted to obtain the B region weighted vector. Determine the mean of the weighted vector of region A; calculate the first distance between the weighted vector of region A and the mean of region A; determine the mean of the weighted vector of region B; calculate the second distance between the weighted vector of region B and the mean of region B; and determine the sum of the first distance and the second distance as the first geographic information evaluation index.

5. The radar geographic information and echo fusion processing sample selection method according to claim 1, characterized in that, The expression for the normalized Doppler frequency is: in, For the flight speed of the carrier aircraft, For wavelength, The pulse repetition frequency, For the first In the distance ring, the first The angle between each information point and the array axis. The angle between the array axis and the carrier direction is denoted by . For the first The pitch angle of each information point on the distance ring; The expression for the range of the plurality of Doppler intervals is: in, s k For the range of intervals, This indicates the number of Doppler intervals that have been divided.

6. A sample selection device for radar geographic information and echo fusion processing, characterized in that, The radar geographic information and echo fusion processing sample selection device includes at least one processor and a memory, which are connected via a data bus. The memory stores instructions that can be executed by the at least one processor. After being executed by the processor, the instructions are used to implement the radar geographic information and echo fusion processing sample selection method according to any one of claims 1-5.

7. A non-volatile computer storage medium, characterized in that, The computer storage medium stores computer-executable instructions, which are executed by one or more processors to perform the radar geographic information and echo fusion processing sample selection method according to any one of claims 1-5.

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