Radar target processing method based on three-dimensional space coordinate hash index

Abstract

The invention relates to a radar target processing method based on a three-dimensional space coordinate hash index, and the method comprises the steps: segmenting a current airspace coverage area into a plurality of airspace blocks according to the memory size of a radar system and a judgment threshold, constructing a hash function according to the features of the airspace blocks, calculating the hash values of all the airspace blocks through employing the hash function, and calculating the hash values of all the airspace blocks; establishing a hash table and a redundancy table according to the conflict of the hash values; and obtaining the hash value of the new target information by using the hash function, searching the hash value of the new target information in the hash table and the redundant table, and determining the storage position of the target in the memory by searching at most twice. According to the method, on one hand, the hash table and the redundancy table are established according to the conflict of the hash values, so that the time in a new target information processing flow is shortened; and on the other hand, the hash value of the new target information is obtained by utilizing the hash function, the hash value of the new target information is searched in the hash table and the redundant table, and the storage position of the target in the memory can be determined by searching at most twice, so that the utilization rate of storage resources is improved.

Description

Technical Field

[0001] The present application relates to the technical field of radar target processing, and in particular to a radar target processing method based on three-dimensional space coordinate hash indexing. Background Art

[0002] After receiving the target echo, the radar system calculates the target's point track information through the real-time signal processor. The target processing computer uses the point track information to form the tracks of multiple targets on the display control machine after processing such as track initiation, point track correlation, and multi-target tracking. In engineering applications, radar signal processing and target processing are strictly constrained by the system's working sequence. Once the processing process times out, the entire system will work abnormally. Therefore, when designing the target processing algorithm, the system's real-time requirements must be met. However, due to the low execution efficiency and resource utilization of existing target processing algorithms, it is often necessary to make a trade-off between the number of targets processed at the same time and the data rate to reduce the system's concurrency and reduce the risk of system real-time performance being destroyed.

[0003] The traditional target processing method is implemented by maintaining multiple target point track information sequence tables. Taking point track correlation as an example, when new point track information arrives, it is necessary to compare it with the latest updated track information in the existing queue according to the judgment criteria to determine the ownership of the point track. This method has the following problems: 1. The execution efficiency of the traversal queue algorithm is low. If the radar has a total of m task modes, each mode needs to maintain n point track queues, and the queue length is l, then the time complexity of performing a point track processing is O(m×n×l). As the radar functions become increasingly complex, the number of task modes and queues continues to increase, and the time overhead of point track processing will further increase. 2. When the system is initialized, the target information in the queue is usually set to zero, resulting in a large amount of memory space being idle and low storage resource utilization. 3. The target position information is only used as a comparison object, not a basis for searching, resulting in increased time overhead and low utilization of effective information. In summary, the existing target processing methods have low efficiency in utilizing various resources and do not maximize the target processing capability of the radar system.

[0004] Therefore, it is necessary to propose a solution to improve one or more problems existing in the above-mentioned related technical solutions.

[0005] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present application, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0006] The purpose of the present disclosure is to provide a radar target processing method based on three-dimensional space coordinate hash indexing, thereby overcoming one or more problems caused by limitations and defects of related technologies at least to a certain extent.

[0007] A radar target processing method based on three-dimensional space coordinate hash indexing provided in an embodiment of the present disclosure includes the following steps:

[0008] The current airspace coverage is determined according to the radar system working sequence and scanning range, and the current airspace coverage is divided into multiple airspace blocks according to the radar system memory size and the decision threshold. Each airspace block is represented by a three-dimensional coordinate set, and the attribution relationship between the three-dimensional coordinates of the target information and the three-dimensional coordinate set of the airspace block is defined;

[0009] A hash function is constructed according to the characteristics of the spatial domain blocks, so that the three-dimensional coordinates of the target information in the same spatial domain block are mapped to the same positive integer, the three-dimensional coordinates of the target information in different spatial domain blocks are mapped to different positive integers, and the number of hash values ​​is equal to the number of spatial domain blocks;

[0010] A hash function is used to calculate the hash values ​​of all airspace blocks, and a hash table and a redundant table are established according to the conflict of hash values, wherein the hash table is used to store the airspace block information corresponding to the hash value when there is no conflict, and the redundant table is used to store the airspace block information corresponding to the hash value when there is a hash conflict;

[0011] The hash function is used to obtain the hash value of the new target information, and the hash value of the new target information is searched in the hash table and the redundant table. The storage location of the target in the memory can be determined by at most two searches.

[0012] In an exemplary embodiment of the present application, dividing the current spatial coverage range into multiple spatial blocks is dividing the current coverage spatial domain into L distance segments, M azimuth segments and N elevation segments, a total of K spatial blocks, where K = L×M×N.

[0013] In an exemplary embodiment of the present application, the decision threshold is determined according to the range segment size ΔR, the azimuth segment size ΔA, and the elevation segment size ΔE of the radar system.

[0014] In an exemplary embodiment of the present application, the spatial block is represented by a three-dimensional coordinate set: S k (R l ,A m ,E n ),

[0015] Among them, k is the spatial block number, k = 0, 1, 2, ..., K-1; l is the range segment number, l = 0, 1, 2, ..., L-1; m is the azimuth segment number, m = 0, 1, 2, ..., M-1; n is the elevation segment number, n = 0, 1, 2, ..., N-1; R represents the target slant range in meters, A represents the azimuth in degrees, and E represents the elevation in degrees.

[0016] In an exemplary embodiment of the present application, the three-dimensional coordinates of the target information are expressed as: i (R,A,E),

[0017] Among them, i is a positive integer, indicating the target number; R represents the target slant range in meters, A represents the azimuth in degrees, and E represents the elevation in degrees.

[0018] In an exemplary embodiment of the present application, the attribution relationship between the three-dimensional coordinates defining the target information and the three-dimensional coordinate set of the airspace block is: i (R,A,E)∈S k (R l ,A m ,E n ), if and only if R l ≤R <R l +ΔR,A m ≤A m +ΔA,E n ≤E <E n +ΔE.

[0019] In an exemplary embodiment of the present application, the construction criteria of the hash function are:

[0020] For any space block, make its corresponding hash value a positive integer;

[0021] For target information belonging to the same spatial domain block, the hash values ​​of the target information are made equal;

[0022] For target information that does not belong to the same spatial domain block, the probability that the hash values ​​of the target information are equal is reduced.

[0023] In an exemplary embodiment of the present application, the step of using a hash function to calculate the hash values ​​of all spatial domain blocks and establishing a hash table and a redundancy table according to the conflict of hash values ​​further includes:

[0024] Calculate the hash values ​​of all airspace blocks and store them in the hash table;

[0025] Use an array to record hash table conflicts, and update the record array accordingly every time a hash value is generated;

[0026] If it is determined that a hash conflict is about to occur, the corresponding hash value is recorded in the redundant table, and the redundant table conflict is also recorded in an array;

[0027] The hash collision status is determined by counting the values ​​of the related record array through histogram.

[0028] In an exemplary embodiment of the present application, in the hash table and the redundant table, the elements in the table are linked lists storing the position information in the airspace block. ​

[0029] In an exemplary embodiment of the present application, the header of the linked list includes the three-dimensional coordinate position of the airspace block, a pointer to a target structure belonging to the airspace block, and a hash conflict flag.

[0030] The present application proposes a radar target processing method based on three-dimensional spatial coordinate hash indexing. On the one hand, by using a hash function to calculate the hash values ​​of all spatial blocks, a hash table and a redundant table are established according to the conflict of hash values, thereby reducing the time in the new target information processing flow; on the other hand, a hash function is used to obtain the hash value of the new target information, and the hash value of the new target information is searched in the hash table and the redundant table. The storage location of the target in the memory can be determined with at most two searches, thereby improving the utilization rate of storage resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0032] Figure 1 A schematic diagram showing the steps of a radar target processing method based on a three-dimensional space coordinate hash index in an exemplary embodiment of the present application is shown;

[0033] Figure 2 A schematic flow chart of a radar target processing method based on three-dimensional space coordinate hash indexing in an exemplary embodiment of the present application is shown;

[0034] Figure 3 A schematic diagram showing the effect of segmenting the airspace in an exemplary embodiment of the present application;

[0035] Figure 4 A histogram showing the number of hits of a hash value in a hash table in an exemplary embodiment of the present application is shown;

[0036] Figure 5 A histogram showing the number of hits of a hash value in a redundant table in an exemplary embodiment of the present application is shown;

[0037] Figure 6 A schematic diagram showing a total time comparison of a single target-related processing between the method of the present application and a traditional method in an exemplary embodiment of the present application is shown. DETAILED DESCRIPTION

[0038] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete and fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0039] In addition, the accompanying drawings are only schematic illustrations of the present application and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0040] This example embodiment provides a radar target processing method based on a three-dimensional space coordinate hash index, such as Figure 1 As shown, the following steps may be included:

[0041] Step S101: Determine the current airspace coverage range according to the radar system working sequence and scanning range, and divide the current airspace coverage range into multiple airspace blocks according to the radar system memory size and the decision threshold. Each airspace block is represented by a three-dimensional coordinate set, and define the attribution relationship between the three-dimensional coordinates of the target information and the three-dimensional coordinate set of the airspace block.

[0042] Step S102: construct a hash function according to the spatial block features, so that the three-dimensional coordinates of the target information in the same spatial block are mapped to the same positive integer, and the three-dimensional coordinates of the target information in different spatial blocks are mapped to different positive integers, and the number of hash values ​​is equal to the number of spatial blocks.

[0043] Step S103: Use a hash function to calculate the hash values ​​of all spatial blocks, and establish a hash table and a redundant table based on the conflict of hash values, wherein the hash table is used to store the spatial block information corresponding to the hash value when there is no conflict, and the redundant table is used to store the spatial block information corresponding to the hash value when there is a hash conflict.

[0044] Step S104: using a hash function to obtain a hash value of the new target information, searching the hash value of the new target information in the hash table and the redundant table, and the storage location of the target in the memory can be determined by searching twice at most.

[0045] The embodiment of the present application proposes a radar target processing method based on three-dimensional spatial coordinate hash index. On the one hand, by using a hash function to calculate the hash values ​​of all spatial blocks, a hash table and a redundant table are established according to the conflict of hash values, thereby reducing the time in the new target information processing flow; on the other hand, a hash function is used to obtain the hash value of the new target information, and the hash value of the new target information is searched in the hash table and the redundant table. The storage location of the target in the memory can be determined with at most two searches, thereby improving the utilization rate of storage resources.

[0046] Below, as Figure 1-Figure 6 As shown, a radar target processing method based on three-dimensional space coordinate hash index proposed in this example embodiment will be described in more detail.

[0047] Step S101: Determine the current airspace coverage range according to the radar system working sequence and scanning range, and divide the current airspace coverage range into multiple airspace blocks according to the radar system memory size and the decision threshold. Each airspace block is represented by a three-dimensional coordinate set, and define the attribution relationship between the three-dimensional coordinates of the target information and the three-dimensional coordinate set of the airspace block.

[0048] Specifically: Determine the current airspace coverage of the radar based on the radar system working sequence and scanning range, and divide the current airspace into L distance segments, M azimuth segments, and N elevation segments according to the system memory size and related decision thresholds, for a total of K airspace blocks. K = L × M × N; each airspace block consists of a three-dimensional coordinate set S k (R l ,A m ,E n ), where k is the spatial block number, k = 0, 1, 2, ..., K-1; l is the range segment number, l = 0, 1, 2, ..., L-1; m is the azimuth segment number, m = 0, 1, 2, ..., M-1; n is the elevation segment number, n = 0, 1, 2, ..., N-1; the range segment size is ΔR, the azimuth segment size is ΔA, and the elevation segment size is ΔE.

[0049] The detected target information is represented by the three-dimensional coordinates O i (R, A, E) description, i is a positive integer, indicating the target number; R in the airspace block and target information represents the target slant range in meters, A represents the azimuth in degrees, and E represents the elevation in degrees; define the attribution relationship O i (R,A,E)∈S k (R l ,A m ,E n ), if and only if R l ≤R <R l +ΔR,A m ≤A m ​+ΔA,E n ≤E <E n +ΔE are established at the same time, the attribution relationship is O i (R,A,E)∈S k (R l ,A m ,E n ) was established.

[0050] Step S102: construct a hash function according to the spatial block features, so that the three-dimensional coordinates of the target information in the same spatial block are mapped to the same positive integer, and the three-dimensional coordinates of the target information in different spatial blocks are mapped to different positive integers, and the number of hash values ​​is equal to the number of spatial blocks.

[0051] Specifically: According to the airspace block S k (R l ,A m ,E n ) features to construct a hash function Hash(), with Hashkey = Hash(S k ); The construction criteria of the hash function are:

[0052] 1. For any k, make Hashkey a positive integer; that is, for any empty space block, make its corresponding hash value a positive integer;

[0053] 2. For any O p ∈S k , O q ∈S k , so that Hash(O p )=Hash(O q );O p and O q For different target information, for target information belonging to the same spatial domain block, the hash values ​​of the target information are made equal;

[0054] 3. For any O p ∈S k , Make Hash(O p )=Hash(O q ) as little as possible, that is, to avoid hash conflicts as much as possible; p and O q For different target information, for target information that does not belong to the same spatial domain block, the probability that the hash values ​​of the target information are equal is reduced.

[0055] The three-dimensional coordinate values ​​of the targets in the same spatial block are mapped to the same positive integer through a hash function, and the three-dimensional coordinate values ​​of the targets in different spatial blocks are mapped to different positive integers. The mapped positive integers are called hash values, and the number of hash values ​​is equal to the spatial block K.

[0056] Step S103: Use a hash function to calculate the hash values ​​of all spatial blocks, and establish a hash table and a redundant table based on the conflict of hash values, wherein the hash table is used to store the spatial block information corresponding to the hash value when there is no conflict, and the redundant table is used to store the spatial block information corresponding to the hash value when there is a hash conflict.

[0057] Specifically: After the hash function is constructed, all spatial blocks are traversed to verify the number of conflicts of the hash function and adjust the parameters of the hash function so that the number of hash conflicts for any spatial block does not exceed 2; at this time, two identical index tables of length K are established in the memory, and the previously designed hash function is used to perform hash calculations on all spatial blocks. When the hash does not conflict, the hash value is used as the index of Table 1, and Table 1 is called a hash table; when the hash conflicts, the hash value generated later is used as the index of Table 2, and Table 2 is called a redundant table. The elements in the table are linked lists that store the position information in the spatial block; the header of the linked list of position information includes the three-dimensional coordinate position of the spatial block, a pointer to the target structure belonging to the spatial block, and a hash conflict flag. The hash conflict flag indicates whether the spatial block has a hash conflict with other spatial blocks. The target structure stores the target's point trace information and the target sequence number in the block. When the index is known, only one search is required to obtain the elements stored in the table, and the search operation of the index table is defined as S key =find(key), where S key It is the empty domain block stored in the table, and the key is the index value.

[0058] Step S104: using a hash function to obtain a hash value of the new target information, searching the hash value of the new target information in the hash table and the redundant table, and the storage location of the target in the memory can be determined by searching twice at most.

[0059] Specifically: For any new target O i , use the hash function designed by the above process to obtain its hash value: Hashkey i =Hash(O i ); then search in the index table: S i =find(Hashkey i ); now check S i The hash conflict flag, if there is no conflict, according to the construction criteria of the hash function, we know that O i ∈S i If there is a conflict, search in the redundant table: S i '=find(Hashkey i ), according to the design principle, we know that O i ∈S i or i ∈S i', only two searches are needed to determine the location of targets close in space in the memory, which is convenient for subsequent processing such as track initiation, point track correlation and target tracking.

[0060] Example 1

[0061] The application of the present invention in a certain type of radar prototype will be described in detail below with reference to the illustrations and simulation comparisons. The target processing flow in the prototype is as follows: Figure 2 As shown, this application is applied to each target-related and queue process of the process according to the following steps, and now takes a single target merge as an example.

[0062] The airspace coverage range of the prototype is determined to be 600m to 6km, -30° to 30° in azimuth, and -10° to 10° in elevation. According to the antenna characteristics of the prototype, the threshold of the prototype is ΔR = 200m, ΔA = 2°, ΔE = 2°. The airspace is divided into blocks according to the threshold, with a total of L = 28 distance segments, M = 31 azimuth segments, N = 11 elevation segments, and a total of K = L × M × N = 9548 airspace blocks. k (R l ,A m ,E n ), where k is the spatial block number, k = 0, 1, 2, ..., K-1; l is the range segment number, l = 0, 1, 2, ..., L-1; m is the azimuth segment number, m = 0, 1, 2, ..., M-1; n is the elevation segment number, n = 0, 1, 2, ..., N-1. The effect of segmenting the spatial domain is as follows: Figure 3 As shown, the three-dimensional coordinate system values ​​in the figure are composed of the airspace block S k (R l ,A m ,E n ) to Cartesian coordinates.

[0063] According to the spatial coverage and the design criteria of the hash function, the designed hash function can be expressed as:

[0064]

[0065] Among them, Mod(n,k) represents the modulus value of k for n; represents rounding x upwards; p 1 ,p 2 ,p 3 Represent three large prime numbers respectively, take p 1 =18397, p 2 =20483, p 3=29303; ΔR, ΔA, ΔE are the distance segment, azimuth segment, and elevation segment sizes during spatial segmentation. Hashkey is the hash value of the three-dimensional coordinates (R, A, E) mapped by the hash function. In other scenarios, the form and parameters of the hash function need to be changed according to the actual situation and the construction criteria of the hash function.

[0066] Use a hash function to hash the used space blocks and perform a conflict check. The specific steps are:

[0067] S10301: Calculate the hash values ​​of all airspace blocks and store them in a hash table; traverse and calculate the hash values ​​of all airspace blocks and store them in a hash table: iniHashkey[i] = hash(S i ),i=1,2,...,K-1;

[0068] S10302: Use an array to record hash table conflicts, and update the record array accordingly each time a hash value is generated; during the traversal calculation process, use an array dupcheck with a length of K to record hash table conflicts, and the method is to increase dupcheck[iniHashkey[i]] by 1 each time an iniHashkey[i] is generated;

[0069] S10303: If it is determined that a hash conflict is about to occur, the corresponding hash value is recorded in the redundant table, and the redundant table conflict situation is also recorded in an array; in the process of traversing calculation and conflict recording, after each new iniHashkey[i] is generated, the value before each dupcheck[iniHashkey[i]] is judged. If the value is not 0, it means that a hash conflict is about to occur. Therefore, iniHashkey[i] needs to be recorded in the redundant table dupHashkey[i], and the redundant table is checked for conflict again in the same way as the conflict check method for the hash table, that is, when a conflict occurs, an array doublecheck with a length of K is used to record the redundant table conflict situation. When the redundant table is assigned dupHashkey[i] = iniHashkey[i], doublecheck[dupHashkey[i]] is incremented by 1. In practical applications, hash conflicts can also be resolved by other solutions such as rehashing.

[0070] S10304: Determine the hash conflict status by counting the values ​​of the related record array through histogram. Use the histogram to count the values ​​stored in dupcheck and doublecheck. The array subscript represents the hash value of a certain empty block. The value stored in this position represents the number of hash value hits. A number of 0 indicates that the hash value of the empty block is equal to the current array subscript. A number of 1 indicates no hash conflict. A number of 2 indicates that a hash conflict occurs once. A redundant table can resolve the conflict. The ideal hash function needs to control the number of conflicts to at most 1, that is, the dupcheck value is 2, and the maximum value of doublecheck is 1. The method used in the system prototype to count the histogram is as follows: Figure 4 and Figure 5 As shown, the horizontal axis in the figure represents the number of hash value hits, and the vertical axis represents the number of times the hit number appears in the hash table or redundant table.

[0071] In this prototype, the method of the present application can realize target correlation by searching and judging the target within the correlation criterion gate twice at most.

[0072] The optimization effect of this application is further illustrated by the following simulation experiments:

[0073] The initial condition of the simulation is to randomly generate N points with a distance of 600m to 6km, an azimuth of -30° to 30°, and an elevation of -10° to 10° as the target information currently captured by the radar. The total time for point correlation with 1000 random targets using the present application and the traditional method is calculated when N=1, 2, ..., 2000. The basis for the decision of point correlation is that the absolute value of the distance difference between the two points is less than or equal to ΔR, the absolute value of the azimuth difference between the two points is less than or equal to ΔA, and the elevation difference between the two points is less than or equal to ΔE. The final simulation results are as follows: Figure 6 As shown, the horizontal axis in the figure represents the number N of target information captured by the radar in the initial conditions of the simulation, and the vertical axis represents the total time of the single target correlation processing of the present application and the traditional method under the current initial conditions. It can be found from the figure that since the time complexity of the algorithm proposed in the present application is O(1), when new target information arrives, the target correlation time does not increase with the increase in the number of targets previously captured by the radar.

[0074] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present application, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0075] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification.

[0076] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary technical means in the art that are not disclosed in the present application.

Claims

1. A radar target processing method based on three-dimensional space coordinate hash indexing, characterized in that: The following steps are involved: The current airspace coverage is determined according to the radar system working sequence and scanning range, and the current airspace coverage is divided into multiple airspace blocks according to the radar system memory size and the decision threshold. Each airspace block is represented by a three-dimensional coordinate set, and the attribution relationship between the three-dimensional coordinates of the target information and the three-dimensional coordinate set of the airspace block is defined; A hash function is constructed according to the characteristics of the spatial domain blocks, so that the three-dimensional coordinates of the target information in the same spatial domain block are mapped to the same positive integer, the three-dimensional coordinates of the target information in different spatial domain blocks are mapped to different positive integers, and the number of hash values ​​is equal to the number of spatial domain blocks; A hash function is used to calculate the hash values ​​of all airspace blocks, and a hash table and a redundant table are established according to the conflict of hash values, wherein the hash table is used to store the airspace block information corresponding to the hash value when there is no conflict, and the redundant table is used to store the airspace block information corresponding to the hash value when there is a hash conflict; The hash function is used to obtain the hash value of the new target information, and the hash value of the new target information is searched in the hash table and the redundant table. The storage location of the target in the memory can be determined by at most two searches.

2. The radar target processing method based on three-dimensional space coordinate hash index according to claim 1, characterized in that: The dividing of the current spatial coverage range into multiple spatial blocks is to divide the current coverage spatial domain into L distance segments, M azimuth segments and N elevation segments, a total of K spatial blocks, where K = L×M×N.

3. The radar target processing method based on three-dimensional space coordinate hash index according to claim 1 is characterized in that: The decision threshold is determined according to the range segment size ΔR, the azimuth segment size ΔA, and the elevation segment size ΔE of the radar system.

4. The radar target processing method based on three-dimensional space coordinate hash index according to claim 1, characterized in that: The spatial block is represented by a three-dimensional coordinate set: S k (R l ,A m ,E n ), Among them, k is the spatial block number, k = 0, 1, 2, ..., K-1; l is the range segment number, = 0, 1, 2, ..., L-1; m is the azimuth segment number, m = 0, 1, 2, ..., M-1; n is the elevation segment number, n = 0, 1, 2, ..., N-1; R represents the target slant range in meters, A represents the azimuth in degrees, and E represents the elevation in degrees.

5. The radar target processing method based on three-dimensional space coordinate hash index according to claim 1 is characterized in that: The three-dimensional coordinates of the target information are expressed as: i (R,A,E), Among them, i is a positive integer, indicating the target number; R represents the target slant range in meters, A represents the azimuth in degrees, and E represents the elevation in degrees.

6. The radar target processing method based on three-dimensional space coordinate hash index according to claim 1 is characterized in that: The attribution relationship between the three-dimensional coordinates defining the target information and the three-dimensional coordinate set of the airspace block is: i (R,A,E)∈S k (R l ,A m ,E n ), if and only if R l ≤R <R l +ΔR,A m ≤A m +ΔA,E n ≤E <E n +ΔE.​ 7. The radar target processing method based on three-dimensional space coordinate hash index according to claim 1 is characterized in that: The construction criteria of the hash function are: For any space block, make its corresponding hash value a positive integer; For target information belonging to the same spatial domain block, the hash values ​​of the target information are made equal; For target information that does not belong to the same spatial domain block, the probability that the hash values ​​of the target information are equal is reduced.

8. The radar target processing method based on three-dimensional space coordinate hash index according to claim 5 is characterized in that: The step of using a hash function to calculate the hash values ​​of all the airspace blocks and establishing a hash table and a redundancy table according to the conflict of the hash values ​​also includes: Calculate the hash values ​​of all airspace blocks and store them in the hash table; Use an array to record hash table conflicts, and update the record array accordingly every time a hash value is generated; If it is determined that a hash conflict is about to occur, the corresponding hash value is recorded in the redundant table, and the redundant table conflict is also recorded in an array; The hash collision status is determined by counting the values ​​of the related record array through histogram.

9. The radar target processing method based on three-dimensional space coordinate hash index according to claim 1, characterized in that: In the hash table and the redundant table, the elements in the table are linked lists storing the position information in the airspace block.

10. The radar target processing method based on three-dimensional space coordinate hash index according to claim 9, characterized in that: The header of the linked list includes the three-dimensional coordinate position of the airspace block, a pointer to a target structure belonging to the airspace block, and a hash conflict flag.

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