Retrieval method for related process of radar data processing

Abstract

The invention relates to a retrieval method for related processes of radar data processing. Comprising the following steps: acquiring track target data obtained by radar data processing software; searching the row chain table according to the azimuth angle of the position data to be stored to select a corresponding row node, searching the column chain table according to the distance of the position data to be stored to select a corresponding column node, and taking the storage position corresponding to the column node as the storage position of the position data, in this way, all position data of the track target data are sequentially stored in the static resource buffer area; when the position data of the track target is retrieved, retrieval is carried out by taking the azimuth angle and the distance of the position data as retrieval pointers in sequence to find out the storage position of the position data, and a retrieval result is output. According to the method, the multi-dimensional index structure is constructed, and key information such as the distance and the azimuth angle in the radar data is used as key values of the index, so that a large amount of radar data is effectively organized and managed, and specific target information can be quickly positioned when needed.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of radar data retrieval, and in particular to a retrieval method for a related process of radar data processing. Background Art

[0002] Radar technology plays a vital role in the field of military reconnaissance. Its core function is to detect and locate targets by transmitting and receiving electromagnetic waves. In this process, the radar system generates a large amount of key data, which contains various important information about the target, such as the target's distance, speed, azimuth, and pitch angle. These data are extremely valuable for military decision-making and action.

[0003] In the current field of radar data processing, a major challenge is the lack of a complete and efficient retrieval algorithm. This defect makes it difficult to quickly locate the required information when retrieving radar data, thus affecting work efficiency and timeliness of decision-making.

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

[0005] It should be noted that this section is intended to provide background or context for the technical solutions of the present invention stated in the claims. The description herein is not admitted to be prior art by inclusion in this section. Summary of the invention

[0006] The object of the present invention is to provide a method for retrieving a related process of radar data processing, thereby solving one or more problems caused by the limitations and defects of the related technology at least to a certain extent.

[0007] The present invention provides a method for retrieving a related process of radar data processing, comprising:

[0008] Acquire track target data obtained by radar data processing software; wherein the track target data includes position data at all time points, and the position data includes at least azimuth and distance;

[0009] According to the azimuth of the position data to be stored, the row linked list is searched to select the corresponding row node, according to the distance of the position data to be stored, the column linked list is searched to select the corresponding column node, and the storage position corresponding to the column node is used as the storage position of the position data, so that all the position data of the track target data are stored in the static resource buffer in sequence;

[0010] When retrieving the position data of the track target, searching the storage location of the position data according to the azimuth and distance of the position data as the search pointer in turn, and outputting the search result;

[0011] Each row node of the row linked list corresponds to an azimuth and a set of column linked lists, each column node of the column linked list corresponds to a distance and a storage location, and the row linked list, the column linked list and the storage location are all allocated to a static resource buffer.

[0012] Optionally, an initialization step is also included:

[0013] Construct an azimuth angle retrieval circular linked list, and pre-allocate storage resources of each row node of the azimuth angle retrieval circular linked list from a static resource buffer;

[0014] Construct a distance retrieval linked list, and pre-allocate storage resources for each column node of the distance retrieval linked list from a static resource buffer;

[0015] Initialize the static resource buffer.

[0016] Optionally, the step of constructing the azimuth retrieval circular linked list includes:

[0017] Initialize the node connection relationship, connect bidirectionally and loop end to end, and add all storage resources to the free travel node list.

[0018] Optionally, the step of constructing a distance retrieval linked list includes:

[0019] Initialize the distance retrieval linked list node connection relationship, bidirectional connection, and add all storage resources to the free column node linked list.

[0020] Optionally, the step of obtaining track target data obtained by radar data processing software includes:

[0021] The position information of the radar target at each time point is calculated according to the track target data, and the position information includes azimuth, distance, pitch angle and speed.

[0022] Optionally, the step of sequentially storing all the position data of the track target data into a static resource buffer includes:

[0023] The storage resource usage of the track target data is estimated according to the static resource allocation method, and available resources are taken from the static resource buffer to pre-allocate storage space for the track target data.

[0024] Optionally, the step of searching the row linked list to select a corresponding row node according to the azimuth angle of the position data to be stored, and searching the column linked list to select a corresponding column node according to the distance of the position data to be stored includes:

[0025] Check whether the column linked list corresponding to the current row node has an available column node;

[0026] If there is no available column node, apply for a new storage space from the static resource buffer for the current column node and update the row information;

[0027] If there is an available column node, point to that column node.

[0028] Optionally, the step of sequentially storing all the position data of the track target data into a static resource buffer includes:

[0029] All the position data of the track target data are stored in sequence, and each time the storage of one position data is completed, the page number information of the column linked list in the row node corresponding to the storage position of the position data is updated until all the position data are stored.

[0030] Optionally, when retrieving the position data of the track target, searching for the storage location of the position data according to the azimuth and distance of the position data as the search pointer in sequence, and outputting the search result includes:

[0031] The azimuth is used as a search pointer, the difference between the current azimuth and the minimum and maximum values ​​of the stored azimuths is calculated, and a search direction is selected according to the difference, and row nodes that meet the current azimuth are queried according to the selected search direction.

[0032] Optionally, when retrieving the position data of the track target, searching for the storage location of the position data according to the azimuth and distance of the position data as the search pointer in sequence, and outputting the search result includes:

[0033] The distance is used as the retrieval pointer for the next stage, and the corresponding column nodes are queried using binary search to obtain the target data.

[0034] The technical solution provided by the present invention may include the following beneficial effects:

[0035] In the present invention, by constructing a multidimensional index structure, key information such as distance and azimuth in radar data is used as index key values, thereby effectively organizing and managing a large amount of radar data, so that specific target information can be quickly located when needed; when the amount of data continues to grow, efficient retrieval performance is still maintained. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present invention, and together with the specification are used to explain the principles of the present invention. Obviously, the accompanying drawings described below are only some embodiments of the present invention, and for those of ordinary skill in the art, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0037] Figure 1 A schematic flow chart showing a retrieval method of a related process of radar data processing in an exemplary embodiment of the present invention;

[0038] Figure 2 A schematic diagram showing a logic determination process of a retrieval method of a correlation process of radar data processing in an exemplary embodiment of the present invention;

[0039] Figure 3 A schematic diagram showing the construction of an azimuth retrieval circular linked list in an exemplary embodiment of the present invention;

[0040] Figure 4 A schematic diagram showing the initialization of an azimuth angle search circular linked list in an exemplary embodiment of the present invention;

[0041] Figure 5 A schematic diagram showing a distance search linked list constructed in an exemplary embodiment of the present invention;

[0042] Figure 6 A schematic diagram showing inserting a column node into a column linked list in an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0043] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the present invention 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.

[0044] In addition, the accompanying drawings are only schematic illustrations of embodiments of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings represent the same or similar parts, and their repeated descriptions 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.

[0045] The present invention provides a method for retrieving the relevant process of radar data processing, referring to Figure 1 As shown in, including:

[0046] Step S100: Acquire track target data obtained by radar data processing software.

[0047] Step S200: Search the row linked list according to the azimuth angle of the position data to be stored to select the corresponding row node, search the column linked list according to the distance of the position data to be stored to select the corresponding column node, and use the storage position corresponding to the column node as the storage position of the position data, so that all the position data of the track target data are stored in the static resource buffer in sequence.

[0048] Step S300: When retrieving the location data of the track target, the storage location of the location data is searched in turn according to the azimuth and distance of the location data as the search pointer, and the search result is output.

[0049] The track target data includes position data at all time points, and the position data includes at least azimuth and distance.

[0050] Each row node of the row linked list corresponds to an azimuth and a set of column linked lists, each column node of the column linked list corresponds to a distance and a storage location, and the row linked list, the column linked list and the storage location are all allocated to a static resource buffer.

[0051] It is important to understand that reference Figure 2 As shown in , this retrieval method is divided into three stages: initialization stage; data processing stage of new track target data; data retrieval stage. Figure 2 The three dashed boxes from top to bottom represent the three stages.

[0052] What also needs to be understood is the data processing stage of the new track target data: the position data received by the data processing software is condensed into a track target through relevant algorithms; available resources are taken out from the static target buffer to pre-allocate storage space for the track target; various types of information (azimuth, distance, pitch angle, speed, etc.) of the target data at each time point are calculated; the current row linked list (azimuth A) is retrieved to select the row that needs to be stored currently; whether the current row linked list has an available column node (distance R) is retrieved, if not, a new space is applied to the static column node resource pool for the column node, and the row information is updated, if so, it points to the node, and the row resource pool stores the fixed column head node; the column to be inserted is selected from many column nodes, and the assigned target node is added to the corresponding position of the column node; various types of information of the target data at each time point, the current row linked list and the current column node are repeatedly calculated.

[0053] It is also necessary to understand that optimization and improvement are specifically made for the real-time problem in radar signal processing. Compared with the traditional traversal algorithm, the present invention shows a significant time advantage when processing a large number of targets (the number of targets is much greater than 500). Specifically, the algorithm can significantly reduce the processing time and improve the response speed of the system by adopting advanced data structures and efficient search strategies, thus having significant advantages in application scenarios with high real-time requirements. This retrieval method not only improves the performance of the radar system, but also can quickly and accurately identify and track targets in complex environments, providing strong technical support for the application of radar systems.

[0054] It is also necessary to understand that the index-based query algorithm of the present retrieval method can not only solve the main challenges currently faced in the field of radar data processing, but also provide more efficient and reliable data support for military reconnaissance, thereby improving the overall combat effectiveness.

[0055] It is also necessary to understand that the core goal of the present invention is to achieve effective classification and storage of radar data, and combine it with corresponding query technology to fully meet various real-time radar monitoring tasks and data processing requirements. Through this innovative method, the management efficiency and query speed of radar data can be greatly improved, ensuring that users can quickly obtain the required information in various complex application scenarios. Specifically, the present invention stores radar data according to specific classification standards so that the data is physically or logically organized into a structure that is easy to retrieve and access. At the same time, with advanced query methods, users can quickly locate and extract relevant data according to different monitoring task requirements, thereby achieving efficient data processing and real-time monitoring. This method not only improves the flexibility and accuracy of data processing, but also provides strong support for the performance optimization of radar monitoring systems.

[0056] It is also necessary to understand that the static resource allocation method of the present invention has significant advantages in resource management, can effectively solve the memory fragmentation problem caused by dynamic resource allocation, and is more efficient and accurate in resource usage, thereby improving the performance and stability of the entire system.

[0057] The retrieval method using the above-mentioned radar data processing related process makes full use of the spatiotemporal characteristics of radar data, aiming to achieve fast and accurate retrieval. Specifically, by constructing a multidimensional index structure, key information such as distance and azimuth in the radar data is used as the key value of the index. In this way, a large amount of radar data can be effectively organized and managed, so that specific target information can be quickly located when needed. In order to further improve the query efficiency, by optimizing the index creation and update process, by adopting efficient data structures and algorithms, the rapid construction and real-time update of the index can be ensured, so that efficient retrieval performance can be maintained even when the amount of data continues to grow. In addition, the scalability and fault tolerance of the index can be increased to cope with complex and changing battlefield environments.

[0058] Next, we will refer to Figures 1 to 6 Each step of the retrieval method of the above-mentioned radar data processing related process in this example embodiment is described in more detail.

[0059] In some embodiments, reference Figure 2 The first dotted box in the figure represents the initialization stage. The retrieval method further includes the initialization step:

[0060] Construct an azimuth retrieval circular linked list, and pre-allocate storage resources for each row node of the azimuth retrieval circular linked list from a static resource buffer.

[0061] Build a distance retrieval linked list and pre-allocate storage resources for each column node of the distance retrieval linked list from a static resource buffer.

[0062] Initialize the static resource buffer.

[0063] It is important to understand that Figure 3 The specific operation details shown are to pre-allocate the azimuth search circular linked list node resource buffer. 1 To A n They represent n row nodes respectively, which are connected in sequence and then connected end to end to form a circular linked list structure.

[0064] In some embodiments, reference Figure 2 The initialization azimuth search linked list shown in , the step of constructing the azimuth search circular linked list includes:

[0065] Initialize the node connection relationship, connect bidirectionally and loop end to end, and add all storage resources to the free travel node list.

[0066] It is important to understand that the specific operational details such as Figure 3 and Figure 4 As shown, the operation of initializing the node connection relationship is performed. Among them, Figure 3 It is a circular linked list structure formed by the row linked list. Figure 4 A is the number of rows in the linked list. 1 For example, determine A 1 The row node's forward pointer points to A 2 , A 1 The back pointer of the row node points to A n .

[0067] In some embodiments, reference Figure 2 The distance retrieval linked list is initialized as shown in , and the step of constructing the distance retrieval linked list includes:

[0068] Initialize the distance retrieval linked list node connection relationship, bidirectional connection, and add all storage resources to the free column node linked list.

[0069] It is important to understand that the specific operation details such as Figure 5 As shown, the operation of initializing the distance retrieval linked list node connection relationship is performed. Among them, R i1 To R in Respectively represent the n column nodes in the i-th row node, and add all resources to the free column node linked list through a bidirectional link.

[0070] In some embodiments, step S100 includes:

[0071] The position information of the radar target at each time point is calculated according to the track target data, and the position information includes azimuth angle A, distance R, pitch angle and speed.

[0072] It should be understood that the position information at each time point may include not only the azimuth angle A, distance R, pitch angle and speed, but also other data information.

[0073] In some embodiments, step S200 includes:

[0074] The storage resource usage of the track target data is estimated according to the static resource allocation method, and available resources are taken from the static resource buffer to pre-allocate storage space for the track target data.

[0075] It should be understood that available resources are taken from the static target buffer to pre-allocate storage space for the track target. The static resource allocation method has significant advantages over the dynamic resource allocation method. Through static resource allocation, the required resource usage can be pre-calculated according to actual needs, thereby effectively avoiding problems such as memory fragmentation that may occur during dynamic resource allocation, thereby affecting system performance. Compared with the traditional traversal algorithm, the static resource allocation method of the present invention is closer to actual needs in resource usage and avoids the problem of pre-allocating too many memory processing resources. Traditional traversal algorithms usually pre-allocate a large amount of memory resources to ensure that there will be no shortage of resources during the processing process. However, this method will cause a large amount of memory resources to be wasted because the resource demand in actual use is often less than the pre-allocated resource amount. Through static resource allocation, the present invention can more accurately control the use of resources, thereby improving resource utilization and reducing memory waste. This method can not only improve the operating efficiency of the system, but also reduce the operating cost of the system. In addition, the static resource allocation method also has better predictability and stability, because the resource usage is pre-calculated and determined, and no unexpected system behavior will occur due to dynamic changes.

[0076] In some embodiments, reference Figure 2 The retrieval distance linked list shown in and stored, step S200 includes:

[0077] Check whether the column linked list corresponding to the current row node has an available column node.

[0078] If there is no available column node, a new storage space is requested from the static resource buffer for the current column node, and the row information is updated.

[0079] If there is an available column node, point to that column node.

[0080] It is important to understand that the query is to see if the current row list has an available column node (distance R). If not, a new space is requested from the static column node resource pool for the column node. The specific operation details are as follows: Figure 6 As shown, the row information is updated. If there is one, it points to the node. The row resource pool stores the fixed column head node. Figure 6 Medium R im To R im+2 They respectively represent the specific positions of the column nodes to be inserted in the i-th column linked list.

[0081] In some embodiments, step S200 includes:

[0082] All the position data of the track target data are stored in sequence, and each time the storage of one position data is completed, the page number information of the column linked list in the row node corresponding to the storage position of the position data is updated until all the position data are stored.

[0083] It is important to understand that the column to be inserted is selected from the many column nodes, and the assigned target node is added to the position corresponding to the column node. Repeat the steps of determining various types of data at the next time point, retrieving the current row list, determining the column node, and updating the page number information of each column in the row until all data is stored.

[0084] In some embodiments, reference Figure 2 The retrieval azimuth pointer shown in and the retrieval direction are determined to find the corresponding linked list. Step S300 includes:

[0085] The azimuth is used as a search pointer, the difference between the current azimuth and the minimum and maximum values ​​of the stored azimuths is calculated, and a search direction is selected according to the difference, and row nodes that meet the current azimuth are queried according to the selected search direction.

[0086] It should be understood that the calculation of the minimum value A of the stored azimuth angle min With the maximum value A max The difference between , and the search direction is determined according to formula (1):

[0087]

[0088] Query the data linked list that matches the current azimuth.

[0089] In some embodiments, reference Figure 2 The retrieval distance pointer and the binary search method shown in FIG. 3 are used to query the current linked list. Step S300 includes:

[0090] The distance is used as the retrieval pointer for the next stage, and the corresponding column nodes are queried using binary search to obtain the target data.

[0091] It is important to understand that through binary search, the middle value of the stored distance is first found, the distance used as the retrieval pointer is compared with the middle value, the search interval is reduced to half of the previous one, a second comparison is made with the middle value, and the search interval is reduced to half of the previous one again until the target data is found.

[0092] 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 invention. 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 different embodiments or examples described in this specification.

[0093] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed by the present invention. The specification and examples are to be considered exemplary only, and the true scope and spirit of the present invention are indicated by the appended claims.

Claims

1. A method for retrieving a related process of radar data processing, characterized in that: include: Acquire track target data obtained by radar data processing software; wherein the track target data includes position data at all time points, and the position data includes at least azimuth and distance; According to the azimuth of the position data to be stored, the row linked list is searched to select the corresponding row node, according to the distance of the position data to be stored, the column linked list is searched to select the corresponding column node, and the storage position corresponding to the column node is used as the storage position of the position data, so that all the position data of the track target data are stored in the static resource buffer in sequence; When retrieving the position data of the track target, searching the storage location of the position data according to the azimuth and distance of the position data as the search pointer in turn, and outputting the search result; Each row node of the row linked list corresponds to an azimuth and a set of column linked lists, each column node of the column linked list corresponds to a distance and a storage location, and the row linked list, the column linked list and the storage location are all allocated to a static resource buffer.

2. The search method according to claim 1, characterized in that: It also includes the initialization steps: Construct an azimuth angle retrieval circular linked list, and pre-allocate storage resources of each row node of the azimuth angle retrieval circular linked list from a static resource buffer; Construct a distance retrieval linked list, and pre-allocate storage resources for each column node of the distance retrieval linked list from a static resource buffer; Initialize the static resource buffer.

3. The search method according to claim 2, characterized in that: The step of constructing the azimuth retrieval circular linked list comprises: Initialize the node connection relationship, connect bidirectionally and loop end to end, and add all storage resources to the free travel node list.

4. The search method according to claim 2, characterized in that: The step of constructing the distance retrieval linked list comprises: Initialize the distance retrieval linked list node connection relationship, bidirectional connection, and add all storage resources to the free column node linked list.

5. The search method according to claim 1, characterized in that: The step of obtaining the track target data obtained by the radar data processing software comprises: The position information of the radar target at each time point is calculated according to the track target data, and the position information includes azimuth, distance, pitch angle and speed.

6. The search method according to claim 1, characterized in that: The step of sequentially storing all the position data of the track target data into the static resource buffer comprises: The storage resource usage of the track target data is estimated according to the static resource allocation method, and available resources are taken from the static resource buffer to pre-allocate storage space for the track target data.

7. The search method according to claim 1, characterized in that: The steps of searching the row linked table according to the azimuth angle of the position data to be stored to select the corresponding row node, and searching the column linked table according to the distance of the position data to be stored to select the corresponding column node include: Check whether the column linked list corresponding to the current row node has an available column node; If there is no available column node, apply for a new storage space from the static resource buffer for the current column node and update the row information; If there is an available column node, point to that column node.

8. The search method according to claim 7, characterized in that: The step of sequentially storing all the position data of the track target data into the static resource buffer comprises: All the position data of the track target data are stored in sequence, and each time the storage of one position data is completed, the page number information of the column linked list in the row node corresponding to the storage position of the position data is updated until all the position data are stored.

9. The retrieval method according to any one of claims 1 to 8, characterized in that: When retrieving the position data of the track target, the steps of searching for the storage location of the position data according to the azimuth and distance of the position data as the search pointer in turn, and outputting the search result include: The azimuth is used as a search pointer, the difference between the current azimuth and the minimum and maximum values ​​of the stored azimuths is calculated, and a search direction is selected according to the difference, and row nodes that meet the current azimuth are queried according to the selected search direction.

10. The search method according to claim 9, characterized in that: When retrieving the position data of the track target, the steps of searching for the storage location of the position data according to the azimuth and distance of the position data as the search pointer in turn, and outputting the search result include: The distance is used as the retrieval pointer for the next stage, and the corresponding column nodes are queried using binary search to obtain the target data.

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