A method and system for processing large amounts of radar data

Abstract

The application discloses a kind of to the processing method and system of large data amount radar data, it is related to radar data processing technical field, by obtaining the real-time data of multiple for target tracking radar and constructing dataset to store, then using BIT information data to the data stored in dataset is washed;Using the target feature data of any radar, lock tracking target, and synchronously obtain corresponding first target track data;When locking tracking target, in the dataset of remaining radar is traversed, obtain the second target track data corresponding to the tracking target;Calculate first track data and the first change in preset time, and the second change of all second track data;Again to the first change and all second change is handled to obtain reference change, to realize the tracking of tracking target.The application can not only realize the efficient processing of mass radar real-time data, but also realize the improvement of target tracking precision and stability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of radar data processing, and in particular to a method and system for processing large amounts of radar data. BACKGROUND

[0002] Radar data processing, referred to as RDP, is a post-processing process of signal processing. The input of the radar data processing process is a target track formed by radar signal processing. The track information includes the distance, azimuth and pitch values of the target, etc. The radar data processing obtains a target track by correlating the measurement sets obtained by multiple scans. After successfully starting the target track, the data processing can correct the measurement errors of the target position and speed of the radar by using a filtering algorithm, and accurately estimate the true information of the target. Through continuous observation of the target, the system can provide information such as the position, speed, acceleration and impact point of the target.

[0003] Not only the real-time data of the radar needs to be processed, but also the stored radar data needs to be processed. By studying the past radar data, the regular characteristics are explored, and the application efficiency and level of the radar data are improved. In general, the radar data processing is to more deeply and systematically understand the detected target, more efficiently capture the target, and more accurately measure the target. However, in order to improve the accuracy and stability of target tracking, it is no longer satisfied to locate the target by a single radar, but to fuse the observation data of multiple radars to improve the accuracy and stability of target tracking. Consequently, the real-time detection data of spatial targets obtained by the radar is increasing in both quantity and variety, and the application efficiency and timeliness of the radar data cannot be guaranteed. Therefore, a method and system for processing large amounts of radar data are urgently needed. SUMMARY

[0004] Therefore, the present application provides a method and system for processing large amounts of radar data to solve the problems in the prior art.

[0005] The first aspect of the present application provides a method for processing large amounts of radar data, comprising:

[0006] Obtaining N real-time data of radars for target tracking, and establishing a data set for storing real-time data for each radar, wherein the real-time data includes target feature data, target track data, BIT information data and environmental parameter data, and N>1;

[0007] Based on the BIT information data, the remaining real-time data in the data set is cleaned;

[0008] Based on the data set after data cleaning, the target feature data in any radar real-time data is obtained as first target feature data, and the target track data corresponding to the first target feature data is obtained as first target track data.

[0009] Based on the first target feature data, a tracking target is locked, and second target feature data corresponding to the tracking target is matched in real-time data of the remaining radars, and corresponding second target track data is synchronously acquired;

[0010] A first change amount of the first target track data in a preset time and a second change amount of all second target track data in the preset time are calculated, a first reference change amount of target track data corresponding to the tracking target is processed based on the first change amount and all second change amounts, and tracking of the tracking target is realized based on the first reference change amount.

[0011] In a possible implementation manner of the first aspect, the method further includes:

[0012] A database for storing all data sets is established;

[0013] Based on the database, target feature data of the same target is acquired as third target feature data, target track data corresponding to all third target feature data is synchronously acquired as third target track data, and corresponding environment parameter data is acquired as first environment parameter data;

[0014] Based on all third target track data and all first environment parameter data, a second reference change amount of third target track data of the same target in different environments is processed by using a first preset method;

[0015] Tracking of the same target is realized based on the second reference change amount.

[0016] In a possible implementation manner of the first aspect, the first preset method includes:

[0017] A plurality of sample targets of the same target are acquired;

[0018] Based on the database, the third target track data and the first environment parameter data of each sample target in different time periods are acquired;

[0019] The first environment parameter data corresponding to each sample target in different time periods is processed to obtain a reference environment parameter;

[0020] In the same reference environment parameter, a mean value of the first reference change amount of third target track data corresponding to all sample targets is calculated to obtain a second reference change amount of the third target track data of the same target in the same environment;

[0021] All reference environment parameters are combined to calculate the second reference change amount of the third target track data of the same target in different environments.

[0022] In a possible implementation manner of the first aspect, the first environmental parameter data corresponding to each sample target in different time periods is processed to obtain the reference environmental parameter, including:

[0023] Any time period is recorded as a first time period, and the first environmental parameter data in the first time period is obtained;

[0024] The first environmental parameter data includes a plurality of environmental parameter sub-data, and an influence coefficient is preset for each environmental parameter sub-data;

[0025] The mean value of each environmental parameter sub-data corresponding to the first environmental parameter data in the first time period is sequentially calculated to obtain a third calculation result;

[0026] Based on the third calculation result, the sum value of the product of the mean value of each environmental parameter sub-data and the corresponding influence coefficient in the first time period is calculated as the reference environmental parameter in the first time period.

[0027] In a possible implementation manner of the first aspect, based on the first target feature data, the tracking target is locked, and the second target feature data corresponding to the tracking target is matched in the real-time data of the remaining radar, including:

[0028] The first target feature data is obtained, and normalization processing is performed under a preset data protocol to obtain a corresponding feature value recorded as a first feature value;

[0029] The target feature data of different targets is obtained in the real-time data of the remaining radar, and normalization processing is performed under the preset data protocol to obtain the feature values of the target feature data corresponding to different targets;

[0030] The similarity between the first feature value and the feature values of the target feature data corresponding to different targets is calculated to obtain a first calculation result;

[0031] Based on the first target feature data, the tracking target is locked, and based on the first calculation result, the second target feature data corresponding to the tracking target is matched in the real-time data of the remaining radar.

[0032] In a possible implementation manner of the first aspect, the first reference change amount of the target point trail data corresponding to the tracking target is processed, including:

[0033] The first change amount and all second change amounts are stored in a preset set;

[0034] The mean value of all change amounts in the preset set is calculated to obtain a mean value change amount;

[0035] sequentially calculate the difference between all the variation amounts in the preset set and the mean variation amount, to obtain a second calculation result;

[0036] based on the second calculation result, filter the variation amount with the smallest difference from the mean variation amount in the preset set, and mark it as a first initial reference variation amount;

[0037] using all the variation amounts in the preset set except the first initial reference variation amount, sequentially perform convolution and on the first initial reference variation amount, and correct the first initial reference variation amount multiple times to obtain a first reference variation amount.

[0038] In a possible implementation manner of the first aspect, based on the BIT information data, cleaning the real-time data remaining in the data set comprises:

[0039] acquire BIT information data in any radar real-time data, and mark it as first BIT information data;

[0040] determine whether the first BIT information data is located in a first preset range, if yes, do not act, and if not, clean the corresponding target track data, target feature data and environment parameter data in the data set.

[0041] In a possible implementation manner of the first aspect, the method further comprises:

[0042] acquire any tracking target, and mark it as a first tracking target, and acquire a first reference variation amount of the first tracking target about target track data;

[0043] perform traversal on the database, and determine whether there is a target same as the first tracking target, if not, track the first tracking target based on the first reference variation amount of the first tracking target about target track data, and if yes, track the first tracking target by using a second preset method.

[0044] In a possible implementation manner of the first aspect, the second preset method further comprises:

[0045] acquire first environment parameter data corresponding to the first tracking target, and synchronously acquire a second reference variation amount of target track data corresponding to a target same as the first tracking target in the database under the first environment parameter data;

[0046] calculating a difference between the first reference variation of the first tracking target with respect to the target track data and the second reference variation of the same target with respect to the target track data, determining whether the difference is within a second preset range, if yes, calculating a mean value between the first reference variation of the first tracking target with respect to the target track data and the second reference variation of the same target with respect to the target track data as the reference variation of the first tracking target with respect to the target track data under the corresponding first environmental parameter data, and realizing tracking of the first tracking target;

[0047] if no, realizing tracking of the first tracking target with the first reference variation of the first tracking target with respect to the target track data.

[0048] The second aspect of the present application provides a processing system for large amount of radar data, comprising:

[0049] a data set unit configured to acquire real-time data of N radars for target tracking, and establish a data set for storing the real-time data for each radar, wherein the real-time data comprises target feature data, target track data, BIT information data and environmental parameter data, and N>1;

[0050] a data cleaning unit configured to clean the remaining real-time data in the data set based on the BIT information data;

[0051] a first target track unit configured to acquire target feature data in real-time data of any radar based on the data set after data cleaning, and mark the target feature data as first target feature data, and mark corresponding target track data of the first target feature data as first target track data;

[0052] a second target track unit configured to lock a tracking target based on the first target feature data, match second target feature data corresponding to the tracking target in real-time data of the remaining radars, and synchronously acquire corresponding second target track data;

[0053] a tracking unit configured to calculate a first variation of the first target track data within a preset time, and a second variation of all second target track data within the preset time, process the first reference variation of the target track data corresponding to the tracking target based on the first variation and all second variations, and realize tracking of the tracking target based on the first reference variation.

[0054] The beneficial effect is that the application discloses a processing method and system for large data amount radar data, real-time data of multiple target tracking radars are acquired and a data set is constructed for storage, BIT information data is used to clean the data stored in the data set, and the rationality of data acquisition is ensured; target feature data of any radar is used to lock and track a target, and first target track data corresponding to the target feature data is synchronously acquired; after the target is locked and tracked, the target feature data of any radar is used to traverse the data set of the remaining radars, and second target track data corresponding to the tracking target is obtained; a first change amount of the first track data in a preset time and a second change amount of all the second track data in the preset time are calculated; the first change amount and all the second change amounts are processed to obtain a reference change amount of the tracking target with respect to the target track, so that the tracking of the tracking target is realized. BRIEF DESCRIPTION OF DRAWINGS

[0055] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only part of the embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of the provided drawings.

[0056] Figure 1 It is a processing method flow diagram for large data amount radar data provided by the embodiment of the present application.

[0057] Figure 2 It is a processing system composition diagram for large data amount radar data provided by the embodiment of the present application. DETAILED DESCRIPTION

[0058] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0059] In this application, the terms such as first and second are used only to distinguish one entity or operation from another, and do not necessarily require or imply these entities or operations to be in any such actual relationship or order. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover the non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment. Without more limitations, the element defined by the statement "includes a" does not exclude the presence of additional identical elements in the process, method, article or equipment including the element.

[0060] Embodiment one

[0061] In the prior art, in order to improve the accuracy and stability of target tracking, it is currently not satisfied to locate the target by a single radar, but to fuse the observation data of multiple radars to improve the accuracy and stability of target tracking, which brings that the real-time detection data and historical detection data of space targets obtained by radars increase in both quantity and variety, and the application efficiency and timeliness of radar data cannot be guaranteed.

[0062] Therefore, the present application provides a method for processing large amount of radar data, as shown in Figure 1 The method comprises the following steps:

[0063] Obtaining N real-time data of radars for target tracking, and establishing a data set for storing real-time data for each radar, wherein the real-time data comprises target feature data, target track data, BIT information data and environmental parameter data, and N>1;

[0064] Based on the BIT information data, the remaining real-time data in the data set is cleaned;

[0065] Based on the data set after data cleaning, the target feature data in any radar real-time data is recorded as first target feature data, and the target track data corresponding to the first target feature data is recorded as first target track data;

[0066] Based on the first target feature data, the tracking target is locked, and the second target feature data corresponding to the tracking target is matched in the real-time data of the remaining radars, and the corresponding second target track data is synchronously obtained;

[0067] The first change amount of the first target track data in a preset time and the second change amount of all the second target track data in the preset time are calculated, and a first reference change amount of the target track data corresponding to the tracking target is obtained based on the first change amount and all the second change amounts, and tracking of the tracking target is realized based on the first reference change amount.

[0068] The N real-time data for tracking radars are acquired and a data set for storing real-time data is established for each radar, which is useful for distinguishing the specific data source when radar data processing is subsequently performed, and the number N is greater than 1 and can be acquired according to actual conditions, which is not limited in the embodiment.

[0069] The real-time data include target feature data, target track data, BIT information data and environmental parameter data, and it should be noted that the target feature data, the target track data, the BIT information data and the environmental parameter data all belong to data types familiar in the field of radars. The target feature data in the real-time data of the radar refers to key information extracted from a radar echo signal and used for describing physical properties and motion states of a target, and is a core basis for identification, classification, tracking and threat assessment of the target by the radar, and can be divided into two categories of motion features and physical features. The motion features reflect the motion state of the target and are a basis for tracking a target track and predicting a motion trend by the radar. The physical features reflect inherent properties of the target and are used for distinguishing target types. The target track data is estimated data of a target position and motion parameters acquired by the radar through emission of electromagnetic waves and reception of a target echo, and is a basis for tracking and identification of the target by the radar. The BIT information data refers to key data collected in real time by a built-in self-checking function of the radar system and used for monitoring a working state and faults of a device, and is a core output of self-diagnosis of the radar system and aims to ensure normal operation of the radar hardware, software and subsystems, discover and locate faults in a timely manner and ensure reliability of a detection and tracking task. The environmental parameter data refers to various types of quantified information of external environmental states when radar data is collected, directly affects propagation of a radar signal, reception quality of a target echo and accuracy of target detection and tracking, and mainly covers meteorological environmental parameters, terrain and object environmental parameters and electromagnetic environmental parameters.

[0070] The real-time data stored in the data set are cleaned by using the BIT information data, specifically, corresponding BIT information data is acquired and it is judged whether it is located in a first preset range, that is, when the corresponding BIT information data exceeds the first preset range, it is indicated that there is a fault in a working state of the radar, at this time, the real-time data collected have a distortion phenomenon, therefore, the data are cleaned to ensure rationality of the collected data.

[0071] Wherein, based on the data set after data cleaning, the target feature data in the real-time data of any radar in the N radars is recorded as the first target feature data, and the target track data corresponding to the first target feature data is recorded as the first target track data; first, the first target feature data is used to lock the tracking target, and then the target feature data corresponding to the tracking target is matched based on the first target feature data in the real-time data of the remaining radars, and the logic is specifically as follows:

[0072] The first target feature data is obtained, and under a preset data protocol, normalization processing is performed to obtain corresponding feature values recorded as first feature values. For example, all data of the first target feature data about physical characteristics is mapped to a unified range, and the mapping method adopts an interval division and assignment method for data. Then, the first feature values are obtained by summing the feature values of the mapped data. The significance of normalizing the data lies in eliminating the order of magnitude bias and distribution difference, thereby providing a more reliable basis for subsequent data analysis, modeling or decision-making. Repeat the above steps to obtain target feature data of different targets in the real-time data of the remaining radars, and perform normalization processing under the same preset data protocol to obtain feature values of the target feature data corresponding to different targets; by calculating the similarity between the first feature value and the feature values of the target feature data corresponding to different targets in the remaining radars, the first target feature data is used to lock the tracking target, and the second target feature data corresponding to the tracking target is matched in the real-time data of the remaining radars by using the similarity calculation result (such as similarity exceeding a set value, which is determined as the same tracking target).

[0073] For calculating the similarity between the first feature value and the feature values of the target feature data corresponding to different targets in the remaining radars, the following formula is used:

[0074]

[0075] The similarity between the first feature value and the feature values of the target feature data corresponding to different targets in the remaining radars is is a constant, is the first feature value, is the feature value of the target feature data corresponding to different targets in the remaining radars;

[0076] And for the feature value of the target feature data corresponding to any target, the following formula is used:

[0077]

[0078] is the feature value of the target feature data corresponding to any target, is a positive integer greater than or equal to 1, is the sub-feature value corresponding to the target feature data, The number of sub-feature values contained in the target feature data in any radar;

[0079] The sub-feature values corresponding to the target feature data in any radar are assigned, that is, all data of the target feature data about physical features are mapped to a unified range, and the mapping mode adopts the mode of interval division and assignment of data, specifically:

[0080] Obtain the target feature data in any radar, and synchronously obtain all target sub-feature data (about physical features) contained in the target feature data and its historical data;

[0081] Based on the historical data, the data range of each target sub-feature data is determined, and the same number of data intervals is divided for each target sub-feature data, and each data interval is assigned according to the numerical value, such as dividing a single target sub-feature data into 5 data intervals and assigning them in turn as 1-5; the above steps realize the unification of the target sub-feature data, which is convenient for subsequent analysis and processing of the target feature data.

[0082] Wherein, after locking the tracking target, the first change amount of the first target track data in the preset time is calculated, and the second change amount of all second target track data in the preset time is calculated, it should be noted that there are multiple second change amounts, and the number is N-1; then the first reference change amount of the tracking target about the target track data is obtained by processing the first change amount and all second change amounts, and finally the tracking of the tracking target is realized based on the first reference change amount, and the processing logic is specifically:

[0083] The first change amount and all second change amounts are stored in a preset set, and the mean value of all change amounts in the preset set is calculated to obtain the mean value change amount; then the difference between all change amounts in the preset set and the mean value change amount is calculated in turn, according to the multiple difference values obtained, the change amount corresponding to the minimum difference value in the preset set is selected as the first initial reference change amount, which indicates that the change amount of the corresponding radar about the target track data is closer to the mean value change amount, and then the first initial reference change amount is convolved and added by using the change amount of the target track data corresponding to the remaining radars to realize multiple corrections of the first initial reference change amount, and the first reference change amount is obtained; the implementation logic of convolution and addition is to smooth the change amount of each radar (suppress noise) by convolution, and then to perform weighted fusion based on radar accuracy, and the core idea is to use weighted fusion to calculate the weighted average value of the change amount of the target track data corresponding to different radars.

[0084] It should be noted that, in the field of radar target track data processing, using convolution and processing belongs to a relatively common means, including: first, data preprocessing is performed, for each radar, the time series is calculated according to the target track data; based on the measurement accuracy, the weight of each radar is determined; the change amount of each radar about the target track data is convolved, and then the smoothed change amount is weighted and fused. The first initial reference change amount is used as the adjustment target in the above technical means, and the change amount of the remaining radar about the target track data is convolved with the adjustment target (i.e., convolution and then weighted fusion) to complete the multiple corrections of the first initial reference change amount, and the first reference change amount is obtained.

[0085] Further, in addition to using radar accuracy for weighted fusion, the embodiment also provides the following weighted fusion method: different weighting coefficients are set for each change amount in the preset set except the first initial reference change, and the setting of the weighting coefficient logic can be distributed according to the size of the difference between each change amount in the preset set and the mean change amount, that is, the change amount closer to the mean change amount in the preset set has a higher weight coefficient, so that the change amount after the weight coefficient distribution has higher accuracy. Then calculate the weighted average value corresponding to all the remaining change amounts in the preset set, that is, sum and average the first initial reference change amount after distributing the weight coefficients to all the remaining change amounts in the preset set, and take the final weighted average value as the first reference change amount of the target track data corresponding to the tracking target, that is, through the first reference change amount, the motion trajectory of the tracking target is predicted, and the tracking of the tracking target is realized.

[0086] Among them, the above embodiment completes the efficient processing of massive radar real-time data, and realizes high-precision tracking of the target, but in the process of tracking the target by radar, there are also massive historical data, by studying these massive historical data, exploring the law characteristics, it has high value to improve the efficiency of radar data application and realize high-precision tracking of the target, therefore, in addition to completing the efficient processing of massive radar real-time data, the embodiment also improves the processing means of massive radar historical data, specifically:

[0087] A database for storing all data sets is established, and by analyzing all target characteristic data of the same target in the database, the second reference change amount of the same target about the target track data in different environments is processed; first, all target characteristic data of the same target are acquired, and all corresponding target track data and corresponding environment parameter data are acquired synchronously; all target characteristic data of the same target are used to lock the same tracking target, the target track data and the corresponding environment parameter data are used to determine the second reference change amount of the same target about the target track data in different environments, and finally the second reference change amount is used to realize tracking of the same target.

[0088] Wherein, about how to deal with the same kind of target in different environments about the second reference change amount of target track data, the embodiment provides the following way: obtain multiple sample targets of the same kind of target, based on the database, obtain the target track data and the corresponding environment parameter data of each sample target in different time periods; using the reference environment parameter, classify different environments, and then calculate the mean value of the first reference change amount of the corresponding target track data of all sample targets under the same reference environment parameter, to obtain the second reference change amount of the target track data of the same kind of target under the same environment, and the second reference change amount of the target track data of the same kind of target under different environments can be obtained by combining all reference environment parameters. It should be noted that the first reference change amount is the same as the first reference change amount in real-time radar data processing, and the processing method will not be described.

[0089] Wherein, the processing of the reference environment parameter includes: obtaining any time period and obtaining the environment parameter data in the first time period, since the environment parameter data contains multiple environment parameter sub-data (such as meteorological environment parameters, terrain and object environment parameters, and electromagnetic environment parameters, meteorological environment parameters include precipitation data, atmospheric data and wind field data, terrain and object environment parameters include terrain feature data and object type data, and electromagnetic environment parameters include electromagnetic interference data, background noise data and propagation loss data), then preset the influence coefficient for each environment parameter sub-data, which can be distributed by analyzing the historical data to obtain the influence weight; then calculate the mean value of each environment parameter sub-data in the first time period and multiply it by the corresponding influence coefficient, and then calculate the sum value as the reference environment parameter in the time period.

[0090] Further, for the first time period, in addition to the conventional mean value calculation method, the mean value of each environment parameter sub-data can also be processed in the following way, which is: constructing a curve graph with time as the coordinate and single environment parameter sub-data as the vertical coordinate, and using a preset software (such as MathSword numerical calculation software) to process the curve graph, to obtain the mean value of single environment parameter sub-data in the first time period, denoted as environment parameter sub-value, and calculate the mean value of each environment parameter sub-data and multiply it by the corresponding influence coefficient, and then calculate the corresponding sum value, the formula is:

[0091]

[0092] For the reference environment parameter, For the mean value of single environment sub-data (environment parameter sub-value), For the influence coefficient corresponding to the environment parameter sub-value, The number of environment parameter sub-data included in the environment parameter data.

[0093] In the embodiment, the first reference change amount of the tracking target is obtained by processing real-time data, and then the database is traversed to query whether there is a same target as the tracking target. If there is, the second reference change amount of the same target as the tracking target is calculated by processing historical data. If there is not, the tracking of the tracking target is realized by using the first reference change amount of the tracking target.

[0094] In the embodiment, if there is a same target as the tracking target in the database, the environment parameter data of the tracking target is obtained by using real-time data, and the second reference change amount of the same target as the tracking target about the target track data in the same environment is matched in the database by using the environment parameter data. It should be noted that the second reference change amount is the same as the second reference change amount involved in the processing of historical data of the radar, and the processing manner is not described again. The difference between the first reference change amount and the second reference change amount is calculated, and it is determined whether the difference is in a preset range. If yes, the average value between the first reference change amount and the second reference change amount is calculated as the reference change amount of the tracking target about the target track data under the environment parameter data, and the tracking of the tracking target is realized. If no, the tracking of the tracking target is realized by using the first reference change amount of the tracking target about the target track data.

[0095] In the embodiment, the massive real-time data and historical data of the radar are efficiently analyzed and processed, so that the application efficiency and level of the radar data are improved, the target can be more efficiently captured, the target can be more accurately measured, and the precision and stability of the target tracking are finally improved.

[0096] In some embodiments, the method further comprises:

[0097] establishing a database for storing all data sets;

[0098] Based on the database, the target feature data of the same target is recorded as third target feature data, and the target track data corresponding to all third target feature data is recorded as third target track data, and the corresponding environment parameter data is recorded as first environment parameter data;

[0099] Based on all third target track data and all first environment parameter data, the second reference change amount of the third target track data of the same target in different environments is obtained by using a first preset method;

[0100] Based on the second reference change amount, the tracking of the same target is realized.

[0101] In some embodiments, the first preset method comprises:

[0102] Obtaining multiple sample targets of the same target;

[0103] Based on the database, obtaining the third target trajectory data and the first environmental parameter data of each sample target at different time periods;

[0104] Processing the first environmental parameter data corresponding to each sample target at different time periods to obtain a reference environmental parameter;

[0105] Under the same reference environmental parameter, calculating the mean value of the first reference change amount of the third target trajectory data corresponding to all sample targets to obtain the second reference change amount of the third target trajectory data of the same target under the same environment;

[0106] By combining all reference environmental parameters, the second reference change amount of the third target trajectory data of the same target under different environments is calculated.

[0107] In some embodiments, processing the first environmental parameter data corresponding to each sample target at different time periods to obtain a reference environmental parameter comprises:

[0108] Any time period is recorded as a first time period, and the first environmental parameter data in the first time period is obtained;

[0109] The first environmental parameter data includes multiple environmental parameter sub-data, and an influence coefficient is preset for each environmental parameter sub-data;

[0110] The mean value of each environmental parameter sub-data corresponding to the first environmental parameter data in the first time period is calculated in sequence to obtain a third calculation result;

[0111] Based on the third calculation result, the sum value of the product of the mean value of each environmental parameter sub-data and the corresponding influence coefficient in the first time period is calculated as the reference environmental parameter in the first time period.

[0112] In some embodiments, based on the first target feature data, the tracking target is locked, and the second target feature data corresponding to the tracking target is matched in the real-time data of the remaining radar, comprising:

[0113] The first target feature data is obtained, and normalized processing is performed under a preset data protocol to obtain a corresponding feature value recorded as a first feature value;

[0114] Obtaining target feature data of different targets in the real-time data of the remaining radar, and performing normalized processing under the preset data protocol to obtain feature values of target feature data corresponding to different targets;

[0115] calculate a similarity between the first feature value and a feature value of target feature data corresponding to a different target, to obtain a first calculation result;

[0116] based on the first target feature data, lock a tracking target, and based on the first calculation result, match second target feature data corresponding to the tracking target in real-time data of the remaining radars.

[0117] In some embodiments, the processing to obtain the first reference change amount of the target point track data corresponding to the tracking target comprises:

[0118] store the first change amount and all second change amounts to a preset set;

[0119] calculate a mean value of all change amounts in the preset set, to obtain a mean value change amount;

[0120] calculate a difference between all change amounts in the preset set and the mean value change amount in sequence, to obtain a second calculation result;

[0121] based on the second calculation result, filter a change amount with a minimum difference from the mean value change amount from the preset set, and mark it as a first initial reference change amount;

[0122] convolve and multiply all change amounts remaining in the preset set except the first initial reference change amount with the first initial reference change amount in sequence, and correct the first initial reference change amount multiple times, to obtain a first reference change amount.

[0123] In some embodiments, based on the BIT information data, the cleaning of the remaining real-time data in the data set comprises:

[0124] obtain BIT information data in any radar real-time data, and mark it as first BIT information data;

[0125] determine whether the first BIT information data is located in a first preset range, if yes, do nothing, and if not, clean target point track data, target feature data and environment parameter data corresponding to the data set.

[0126] In some embodiments, the method further comprises:

[0127] obtain any tracking target, and mark it as a first tracking target, and obtain a first reference change amount of the first tracking target with respect to target point track data;

[0128] Traverse the database to determine whether there is a same target as the first tracking target, if not, track the first tracking target based on the first reference change amount of the first tracking target about target track data, if yes, track the first tracking target by using a second preset method.

[0129] In some embodiments, the second preset method further comprises:

[0130] Obtain the first environment parameter data corresponding to the first tracking target, and synchronously obtain the second reference change amount of the target track data corresponding to the same target as the first tracking target in the database under the first environment parameter data;

[0131] Calculate the difference between the first reference change amount of the first tracking target about target track data and the second reference change amount of the corresponding same target about target track data, determine whether the difference is within a second preset range, if yes, calculate the mean value between the first reference change amount of the first tracking target about target track data and the second reference change amount of the corresponding same target about target track data as the reference change amount of the first tracking target about target track data under the corresponding first environment parameter data, and track the first tracking target;

[0132] If not, track the first tracking target by using the first reference change amount of the first tracking target about target track data.

[0133] Embodiment two

[0134] Based on the method for processing large amount of radar data provided in Embodiment one of the present application, correspondingly, Embodiment two of the present application further provides a processing system for large amount of radar data, as shown in Figure 2 The processing system comprises:

[0135] A data set unit is configured to obtain real-time data of N radars for target tracking, and establish a data set for storing real-time data for each radar, wherein the real-time data comprises target feature data, target track data, BIT information data and environment parameter data, and N>1.

[0136] A data cleaning unit is configured to clean the remaining real-time data in the data set based on the BIT information data.

[0137] A first target track unit is configured to obtain target feature data in real-time data of any radar based on the data set after data cleaning, and record the target feature data as first target feature data, and record target track data corresponding to the first target feature data as first target track data.

[0138] The second target track unit is configured to lock and track a target based on the first target feature data, and match second target feature data corresponding to the tracked target in real-time data of the remaining radars to synchronously obtain corresponding second target track data.

[0139] The tracking unit is configured to calculate a first variation of the first target track data within a preset time and a second variation of all the second target track data within the preset time, and obtain a first reference variation of target track data corresponding to the tracked target based on the first variation and all the second variation, and realize tracking of the tracked target based on the first reference variation.

[0140] The above-described specific principles and execution processes of each unit in the processing system for large amount of radar data disclosed in Embodiment Two of the present application are the same as those in the processing method for large amount of radar data disclosed in Embodiment One of the present application, and can be referred to the corresponding parts in the processing method for large amount of radar data disclosed in Embodiment One of the present application, which will not be repeated here.

[0141] Those skilled in the art will further appreciate that the individual steps of the example units and algorithm steps described in connection with the embodiments disclosed herein can be realized by electronic hardware, computer software, or any combination thereof. To clearly illustrate the interchangeability of hardware and software, and to avoid obscuring the disclosure, the various examples have been described generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the particular application and design constraints imposed on the overall system. Those skilled in the art can implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

[0142] While the preferred embodiments of the application have been described, additional variations and modifications can be made to the embodiments without departing from the spirit and scope of the application. Therefore, it should be understood that the application is not intended to be limited to the particular forms disclosed. Rather, the intention is to cover all modifications, equivalents and alternatives falling within the spirit and scope of the application as defined by the appended claims and their equivalents.

[0143] Obviously, various modifications and changes can be made to the present application by those skilled in the art without departing from the spirit and scope of the present application. Thus, it is intended that the present application encompass all such modifications and changes and, accordingly, the application is not limited to the specific embodiments described herein.

Claims

1. A method for processing large amounts of radar data, characterized by The method comprises: acquiring N sets of real-time data for target tracking radars, and establishing a data set for storing the real-time data for each radar, the real-time data comprising target feature data, target track data, BIT information data and environmental parameter data, N > 1; based on the BIT information data, cleaning the remaining real-time data in the data set; based on the data set after data cleaning, acquiring target feature data in any radar real-time data as first target feature data, and corresponding target track data of the first target feature data as first target track data; based on the first target feature data, locking a tracking target, and matching second target feature data corresponding to the tracking target in real-time data of the remaining radars, and synchronously acquiring corresponding second target track data; calculating a first change amount of the first target track data within a preset time, and a second change amount of all second target track data within the preset time; based on the first change amount and all second change amounts, processing to obtain a first reference change amount of target track data corresponding to the tracking target, and based on the first reference change amount, tracking the tracking target; the method further comprises: establishing a database for storing all data sets; based on the database, acquiring target feature data of the same target as third target feature data, and synchronously acquiring target track data corresponding to all third target feature data as third target track data, and corresponding environmental parameter data as first environmental parameter data; based on all third target track data and all first environmental parameter data, using a first preset method to process to obtain a second reference change amount of third target track data of the same target under different environments; based on the second reference change amount, tracking the same target; the first preset method comprises: acquiring multiple sample targets of the same target; based on the database, acquiring the third target track data and the first environmental parameter data of each sample target under different time periods; processing the first environmental parameter data corresponding to each sample target under different time periods to obtain a reference environmental parameter; under the same reference environmental parameter, calculating the mean value of the first reference change amount of the third target track data corresponding to all sample targets to obtain the second reference change amount of the third target track data of the same target under the same environment; collecting all reference environmental parameters to calculate the second reference change amount of the third target track data of the same target under different environments; based on the first target feature data, locking a tracking target, and matching second target feature data corresponding to the tracking target in real-time data of the remaining radars comprises: acquiring the first target feature data, and performing normalization processing under a preset data protocol to obtain corresponding feature values as first feature values; acquiring target feature data of different targets in real-time data of the remaining radars, and performing normalization processing under the preset data protocol to obtain feature values of target feature data corresponding to different targets; Calculate the similarity between the first characteristic value and the characteristic value of the target characteristic data corresponding to different targets to obtain a first calculation result; Based on the first target characteristic data, lock and track the target, and based on the first calculation result, match the second target characteristic data corresponding to the tracked target in the real-time data of the remaining radars.

2. The method of claim 1, wherein, The first environmental parameter data corresponding to each sample target in different time periods is processed to obtain the baseline environmental parameter, which includes: Any time period is recorded as a first time period, and the first environmental parameter data in the first time period is obtained; The first environmental parameter data includes a plurality of environmental parameter sub-data, and a preset influence coefficient is set for each environmental parameter sub-data; The mean value of each environmental parameter sub-data corresponding to the first environmental parameter data in the first time period is calculated in sequence to obtain a third calculation result; Based on the third calculation result, the sum value of the product of the mean value of each environmental parameter sub-data and the corresponding influence coefficient in the first time period is calculated as the baseline environmental parameter in the first time period.

3. The method of claim 1, wherein, The first baseline change amount of the target track data corresponding to the tracked target includes: Store the first change amount and all second change amounts in a preset set; Calculate the mean value of all change amounts in the preset set to obtain a mean value change amount; The difference between all change amounts in the preset set and the mean value change amount is calculated in sequence to obtain a second calculation result; Based on the second calculation result, filter the change amount with the smallest difference from the mean value change amount in the preset set, and record it as the first initial baseline change amount; Using all change amounts in the preset set except the first initial baseline change amount, the first initial baseline change amount is convolved and added in sequence to correct the first initial baseline change amount multiple times to obtain the first baseline change amount.

4. The method of claim 1, wherein, Based on the BIT information data, the real-time data remaining in the data set is cleaned, which includes: Get the BIT information data in any radar real-time data as the first BIT information data; Determine whether the first BIT information data is within a first preset range. If yes, do nothing. If not, clean the target track data, target characteristic data and environmental parameter data corresponding to the data set.

5. The method of claim 1, wherein, The method further includes: Get any tracking target as the first tracking target, and get the first baseline change amount of the first tracking target with respect to the target track data; Iterate through the database to determine whether there is a target identical to the first tracking target. If not, track the first tracking target based on the first baseline change amount of the first tracking target with respect to the target track data. If yes, use a second preset method to track the first tracking target.

6. The method of claim 5, wherein, The second preset method further includes: Get the first environmental parameter data corresponding to the first tracking target, and synchronously get the second baseline change amount of the target track data corresponding to the target identical to the first tracking target in the database under the first environmental parameter data; The difference between the first reference change amount of the first tracking target with respect to the target track data and the second reference change amount of the corresponding same target with respect to the target track data is calculated, and it is determined whether the difference is within a second preset range. If yes, the average value between the first reference change amount of the first tracking target with respect to the target track data and the second reference change amount of the corresponding same target with respect to the target track data is calculated as the reference change amount of the first tracking target with respect to the target track data under the corresponding first environmental parameter data, and the tracking of the first tracking target is realized. If no, the first reference change amount of the first tracking target with respect to the target track data is used to realize the tracking of the first tracking target.

7. A system for processing large volume of radar data, implemented by the method for processing large volume of radar data according to claim 1, characterized in that, The method comprises: a data set unit configured to obtain N sets of real-time data for target tracking radars, and establish a data set for storing the real-time data for each radar, wherein the real-time data comprises target feature data, target track data, BIT information data and environmental parameter data, and N>1; a data cleaning unit configured to clean the remaining real-time data in the data set based on the BIT information data; a first target track unit configured to obtain target feature data in any radar real-time data as first target feature data based on the data set after data cleaning, and obtain target track data corresponding to the first target feature data as first target track data; a second target track unit configured to lock a tracking target based on the first target feature data, match second target feature data corresponding to the tracking target in real-time data of the remaining radars, and synchronously obtain corresponding second target track data; a tracking unit configured to calculate a first change amount of the first target track data within a preset time, and a second change amount of all second target track data within the preset time; based on the first change amount and all second change amounts, a first reference change amount of target track data corresponding to the tracking target is processed, and the tracking of the tracking target is realized based on the first reference change amount.

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