CN112130141A - Airborne radar alarm device adopting front-end and back-end parallel processing mechanism and data processing method thereof - Google Patents

Abstract

The airborne radar alarm device adopting the front-end and back-end parallel processing mechanism comprises an antenna, a receiving and measuring module, a data processing part module, a terminal module and a threat data updating module. The data processing method of the airborne radar alarm device adopting the front-end and back-end parallel processing mechanism is also provided. The method comprises the steps that the radar radiation source full-pulse parameter flow data which are intercepted and received by front-end alarm processing are subjected to data processing by adopting a low-complexity and high-timeliness quick sorting, identification and threat assessment algorithm, so that quick alarm is realized, and timeliness of alarm is emphasized; and the back end alarms process the monitored and received radar radiation source pulse full pulse parameter flow data and intermediate frequency signal data, and the front end sorting unsuccessfully sorted and unsuccessfully identified data. The invention can realize the quick front-end alarm, the accurate rear-end alarm and the online update of the threat database, effectively solves the problems of low data utilization rate and low alarm accuracy of the data processing architecture of the existing airborne radar alarm, and improves the situation perception capability of the airborne platform.

Description

An Airborne Radar Warning Device Using Front-end and Back-end Parallel Processing Mechanism and Its Data Processing management method

technical field

The invention relates to the technical field of airborne self-defense electronic countermeasure engineering applications, in particular to an airborne radar warning device and a data processing method thereof using a front-end and back-end parallel processing mechanism.

Background technique

The airborne radar warning device is an important airborne sensor, which provides the pilot with information such as the type, orientation and working status of the threat by intercepting, measuring and analyzing the radar signal irradiated to the airborne platform. The airborne radar warning device has the advantages of long detection distance, concealed detection, and omnidirectional reception. The pilot can obtain the type, quantity and status of the threat target in the battlefield environment according to the warning information of the airborne radar warning device, so as to conduct electronic interference, missile Combat decisions such as attack and tactical evasion. Therefore, in the process of obtaining the electromagnetic situation on the battlefield, sensing threat information and making tactical decisions, the airborne radar warning device plays a key role, and its technical level plays an important role in the outcome of the battle.

Since the U.S. military first equipped the AN/APR-258 radar warning device in the Vietnam War, the airborne radar warning device has gone from simply receiving radar radiation to being able to identify radar types and sort threats, thereby improving the ability to adapt to dense pulse streams and realizing digital channels. The three developmental stages of the reception. However, with the development of military science and technology, airborne radar alarms face dual challenges from the battlefield environment and game opponents: on the one hand, the battlefield environment is increasingly complex, the types and numbers of radiation sources increase sharply, the signal density increases significantly, and the signal waveform On the other hand, the development of the opponent radar is changing with each passing day. The application of new technologies such as phased array, low interception, and spectrum broadening makes the radar signal increasingly complex and concealed. The signal interception, measurement and analysis of the airborne radar warning device Work brings great challenges. The existing airborne radar warning device data processing architecture is difficult to achieve fast and accurate processing of massive and complex radar signals, and the combat effectiveness is significantly reduced, and a new round of technological innovation is urgently needed. Therefore, it is of great significance to develop a new data processing method of airborne radar warning device to help improve the information perception ability, tactical decision-making ability and battlefield survivability of combat aircraft and pilots.

SUMMARY OF THE INVENTION

In order to overcome the deficiencies of the prior art, the present invention provides an airborne radar alarm device using a front-end and back-end parallel processing mechanism, including an antenna, a receiving measurement module, a data processing part module, a terminal module, and a threat data update module; wherein

Antennas for intercepting radar radiation source signals in space;

The receiving measurement module converts the radio frequency or high frequency signal intercepted by the antenna into a digital signal, measures the frequency, arrival time, pulse width, angle of arrival, direction of arrival, intermediate frequency parameters and other parameter information of the signal, and forms a pulse parameter stream and outputs it ;

The data processing module sorts the pulse parameter stream processed by the receiving measurement module, sorts the parameters of a single radiation source from the aliased pulse parameter stream, and performs template matching with the threat database to realize the detection of radar radiation sources. Identify, and then perform threat assessment according to the identification result, and output the result of the threat assessment to the terminal module;

Terminal modules, which provide threat information to other devices/systems through video or audio information;

The threat data update module, according to the radiation source data obtained from the accurate identification of the back-end alarm module, after a certain number of repeated occurrences is confirmed, it is written into the threat database to realize the update of the threat data.

A data processing method for an airborne radar warning device using the above-mentioned airborne radar warning device using a front-end and rear-end parallel processing mechanism is also provided. The specific process of the data processing is as follows:

(1) After the detected pulse flow is measured by the receiving measurement module, a pulse parameter flow is formed. The pulse parameter flow includes the full pulse parameter flow and the intermediate frequency data flow; the full pulse parameter flow and the intermediate frequency data flow are sent to the back-end alarm module. The front-end alarm module only receives the full pulse parameter stream;

(2) The processing process of the front-end alarm module:

(a) Perform front-end sorting on the full pulse parameter stream; continue to perform front-end identification on the data that is successfully sorted, and send the data that is not successfully sorted into the back-end alarm module for back-end sorting, and further fine-tune sorting;

(b) Perform front-end identification on the successful sorting data; match the radar radiation source information in the threat database according to the sorting parameters, and if the matching is successful, perform front-end threat assessment on the successfully matched data, that is, perform threat level calculation and sorting, and match Unsuccessful data is sent to the back-end identification of the back-end alarm module for accurate identification;

(c) Perform front-end threat assessment on the matching successful data, and output the judgment result to the terminal module in the form of alarm information;

(3) The processing process of the back-end alarm module:

The back-end alarm module has a modular and scalable back-end sorting algorithm library, back-end identification algorithm library and threat assessment algorithm library;

(a) Use the algorithm in the back-end sorting algorithm library to perform back-end sorting on the full-pulse parameter stream, the intermediate frequency data stream, and the unsorted data; Select the fusion result data to continue the back-end identification, and use the back-end identification algorithm library to carry out the back-end identification. In this process, the data that is not successfully sorted is filtered out as clutter data;

(b) There are three sources of processing data for back-end identification: data of unsuccessful front-end identification, data of sorting and fusion results, and airborne bus data from airborne radar, IFF, and data link terminal; The obtained identification fusion result data is sent to the back-end threat assessment, and the threat assessment algorithm library is used for threat determination, and the identification fusion result data is sent to the threat data update module for storage;

(c) using multiple threat assessment algorithms to perform back-end threat assessment on the identification fusion result data; after the judgment results of multiple algorithms are fused, a fused threat assessment result is formed, which is output to the terminal module in the form of alarm information;

(4) Processing process of the threat data update module: The threat data update module receives the identification and fusion result data, and according to the update criterion of "recurrence and repeated confirmation", when the number of repeated occurrences of a certain radiation source data reaches the set K times Then, the radiation source parameter is written into the threat database in the front-end identification in the front-end alarm module to realize the online update of the threat database.

One of the features of the above airborne radar alarm data processing method is that the front-end alarm and the back-end alarm are processed in parallel, and the tasks of sorting, identification and threat assessment are performed in parallel at the front-end and the back-end.

Another feature of the above airborne radar warning device data processing method is that the front end adopts the sorting, identification and threat assessment algorithm of the existing airborne radar warning device to ensure the real-time nature of the warning, and the back end adopts a modular complex algorithm to reduce the real-time performance. requirements to improve the accuracy of alarms.

Another feature of the above airborne radar warning device data processing method is that: back-end sorting, back-end identification and back-end threat assessment processing in back-end warning processing all use a modular and scalable algorithm library, and multiple algorithms are used. The processing results are fused; specifically, its modularity is reflected in the use of multiple algorithm modules for independent and parallel sorting, identification and threat assessment tasks, each algorithm is a separate algorithm module, and the output results are fused to form a fusion system. Fusion results of sorting, identification and threat assessment; its scalability is reflected in the fact that each algorithm in the algorithm library can be run as a separate algorithm module, and the algorithm modules can be added or deleted as needed to achieve the expansion of the entire identification algorithm library Its fusion is reflected in the independent operation and calculation of the algorithm modules in the sorting, identification and threat assessment algorithm library, and the processing results of multiple algorithm modules are fused and judged, so as to realize the mutual verification of the processing results of each module.

Another feature of the above airborne radar warning device data processing method is that: in the back-end identification processing in the back-end warning, other airborne sensor data is introduced to perform information fusion with the data of the airborne radar warning device itself.

The method of the invention adopts the design of "front-end and back-end" parallel alarm, modular expansion and online update of threat database, which can realize rapid sorting, accurate identification and accurate alarm processing of massive and dense radar signals. These innovations enhance the invention generality.

Description of drawings

Fig. 1 Model of airborne radar warning device;

Fig. 2 existing airborne radar warning device data processing model;

Figure 3 is a data processing architecture diagram of an existing airborne radar warning device;

Figure 4 adopts the data processing model of the airborne radar warning device using the front-end and back-end parallel processing mechanism;

Fig. 5 is the data processing flow chart of the airborne radar warning device using the front-end and back-end parallel processing mechanism;

Figure 6 is a diagram of the data processing architecture of the airborne radar warning device using the front-end and back-end parallel processing mechanism.

Detailed ways

The present invention will be further described below in conjunction with the accompanying drawings.

1. The composition of the airborne radar warning device using the front-end and back-end parallel processing mechanism

The airborne radar alarm mainly includes an antenna, a receiving measurement module, a data processing part module, and a terminal module. Its basic model is shown in Figure 1. The antennas include direction finding antennas and special antennas, which are used to intercept radar radiation source signals in space. The receiving measurement module converts the radio frequency or high frequency signal intercepted by the antenna into a digital signal, measures the frequency, arrival time, pulse width, arrival angle, arrival direction and other parameter information of the signal, and forms the full pulse parameter and outputs it. The data processing module sorts the full-pulse parameter stream processed by the receiving measurement module, sorts the parameters of a single radiation source from the aliased full-pulse parameter stream, and performs template matching with the threat database to realize the detection of radar radiation sources. Identify, and then perform threat assessment according to the identification result, and output the result of the threat assessment to the terminal module. The terminal module provides threat information to other devices/systems, such as pilots, through video or audio information.

The data processing of the airborne radar alarm is mainly carried out in the data processing module. The data processing process mainly includes signal sorting, radiation source identification and threat assessment. The basic model is shown in Figure 2. The data processing architecture of the existing airborne radar alarm uses a fast sorting and identification algorithm to process the detected data and give an alarm. Among them, the signal sorting is realized by the correlation comparison pre-selection and the sequence search main sorting algorithm, the radiation source identification is realized by the template matching method, the threat assessment is based on the pre-determined evaluation criteria, and the threat level is calculated according to the calculation result of the threat level. The threat level of the radiation source is sorted, and the alarm information is output. The processing methods involved in this paragraph belong to existing mature technologies and are well known to those skilled in the art, and will not be repeated here. The specific data processing architecture is shown in FIG. 3 .

2. The data processing method of the airborne radar warning device using the front-end and back-end parallel processing mechanism

Under the data processing architecture of the existing equipment, the alarm algorithm focuses on real-time. Due to the limitation of processing time, it does not support algorithms with high complexity, and it is difficult to realize the refined processing of the detected data. Therefore, the data utilization rate is not high and accurate. The performance is not high, and it is difficult to meet the combat needs in a complex electromagnetic environment. In order to overcome these shortcomings, the present invention adopts the data processing method of the airborne radar warning device based on the front-end and back-end parallel processing mechanism. Fig. 4 is the composition model of the airborne radar warning device using the front-end and rear-end parallel processing mechanism. Compared with the single-line warning processing method of the existing airborne radar warning device, the present invention adopts the front-end warning and the back-end warning parallel processing mechanism. Perform sorting, identification, and threat assessment tasks in parallel with the backend. The front-end adopts the sorting identification and threat assessment algorithm of the existing airborne radar alarm to ensure the real-time performance of the alarm, and the back-end adopts a modular and complex algorithm to reduce the real-time requirements and improve the accuracy of the alarm. At the same time, the present invention also has a threat data update module, which can be written into the threat database after a certain number of repeated occurrences is confirmed according to the radiation source data obtained in the accurate identification in the background to realize the update of the threat data.

FIG. 5 is a flow chart of data processing of the airborne radar warning device using the front-end and back-end parallel processing mechanism. The specific process of data processing is as follows:

(1) After the detected pulse flow is measured by the receiving measurement module, a pulse parameter flow is formed. The pulse parameter stream includes the full pulse parameter stream and the intermediate frequency data stream. The full pulse parameter stream and the intermediate frequency data stream are sent to the back-end alarm module, and the front-end alarm module only receives the full pulse parameter stream.

(2) The processing process of the front-end alarm module:

(a) Front-end sorting adopts the correlation comparison pre-selection and sequence search main sorting algorithm in the existing airborne radar alarm device. This method is well known to those skilled in the art and will not be repeated. For details, please refer to the editor-in-chief Wang Xing , Chapter 5, Section 3 of "Principles of Avionics Countermeasures" published by National Defense Industry Press, and chapter 3 and 4 of Chapter 4 of "Principles of Radar Countermeasures (Second Edition)", edited by Zhao Guoqing, published by Xidian University Press Festival. The data that is successfully sorted continues to be identified by the front-end, and the data that is not successfully sorted is sent to the back-end sorting of the back-end alarm module for refined sorting;

(b) The front-end identification adopts the template matching identification method in the existing airborne radar alarm device. This method is well known to those skilled in the art and will not be described again. For details, please refer to the work by Wang Xing et al., published by National Defense Industry Press Chapter 4, Section 1 of "Avionics Countermeasures Networking". According to the sorting parameters and the radar radiation source information in the threat database, match the radar radiation source information in the threat database. If the matching is successful, the front-end threat assessment is performed, that is, the threat level is calculated and sorted. The unsuccessful data is sent to the back-end identification of the back-end alarm module for accurate identification. ;

(c) The front-end threat assessment uses the existing threat level calculation and sorting algorithm to determine the threat. This method is well known to those skilled in the art and will not be repeated. For details, please refer to Cheng Libin and Lin Chunying in Modern Defense Technology, 2006, No. The paper "A Preliminary Study on the Threat Assessment Method of Electronic Warfare Targets" published in the sixth issue of the volume, and output the judgment result to the terminal module in the form of alarm information.

(3) The processing process of the back-end alarm module:

The back-end alarm module has a modular and extensible library of sorting, identification and threat assessment algorithms.

(a) Back-end sorting receives the full pulse parameter stream and the intermediate frequency data stream from the receiving measurement module, as well as the data that was unsuccessfully sorted in the front-end sorting. The back-end sorting adopts a modular and scalable sorting algorithm library. The algorithm modules in the algorithm library use sorting algorithms with high complexity, such as fuzzy C-means clustering, support vector clustering, grid density clustering, etc. The clustering algorithm performs fine sorting, and each algorithm module performs sorting independently. There are many research results of the above sorting algorithms, which are familiar to those skilled in the art and will not be described again. You can refer to Xidian University Zhang Yongqiang's master's thesis "Research on Signal Sorting Algorithms of Unknown Radiation Sources" and Feng Xiaoxiao's master's thesis "Radar" Research on Signal Sorting Algorithms, etc. After the end of the sorting results, data fusion is carried out. The fusion algorithm can use Dempster-Shafer evidence fusion, voting fusion and other fusion methods. These two methods are well known to those skilled in the art and will not be repeated here. The data is sent to the back-end identification, and the back-end identification algorithm library is used for the back-end identification. In this process, the data that is not successfully sorted is filtered as the clutter data. The back-end sorting algorithm library has the characteristics of modularity and scalability. Specifically, its modularity is reflected in the use of multiple sorting algorithms to finely sort the input full pulse parameter stream and intermediate frequency data stream. Each algorithm is Separate algorithm module, the output results are fused to form a fused sorting and fusion result and output to the back-end identification module; its scalability is reflected in the fact that each sorting algorithm in the algorithm library can be run as a separate algorithm module, Algorithm modules can be added or deleted as needed to realize the expansion of the entire sorting algorithm library;

(b) There are three sources of processed data for back-end identification: the radiation source parameters that are not successfully identified by the front-end alarm module’s front-end identification, the radiation source parameters selected by the back-end, and the parameters from the airborne radar, IFF, data link end The onboard bus data of the machine. The back-end identification adopts a modular and extensible identification algorithm library. The algorithm modules in the algorithm library adopt identification algorithms with high complexity, such as neural network algorithm, support vector machine algorithm, and nearest neighbor radiation source identification algorithm in sub-bands. Accurate identification, the above-mentioned identification algorithms have many research results, which are well known to those skilled in the art and will not be repeated. For details, please refer to the fourth chapter in "Avionics Countermeasures Networking" published by the National Defense Industry Press, written by Wang Xing et al. Sections two, three, and four. Each algorithm module is recognized independently, and the recognition results are fused after the end. The fusion algorithm can adopt fusion methods such as Dempster-Shafer evidence fusion and voting fusion. These two methods are well known to those skilled in the art and will not be repeated here. The identification fusion result data is sent to the back-end threat assessment, and the threat assessment algorithm library is used to determine the threat. At the same time, the identification fusion result data is sent to the threat data update module for storage. The back-end recognition algorithm library has the characteristics of modularity and scalability. Specifically, its modularity is reflected in the use of multiple recognition algorithms to accurately recognize the input data. Each algorithm is a separate algorithm module, and the output results are fused. The fusion result of identification and fusion is output to the back-end threat assessment module; its scalability is reflected in the fact that each identification algorithm in the algorithm library can be run as a separate algorithm module, and the algorithm module can be added or deleted as needed to realize the whole Extension of the identification algorithm library;

(c) Back-end threat assessment is based on the existing threat level calculation and sorting algorithms and other algorithms with high complexity, such as multi-attribute decision-making algorithms, combined evaluation methods, cloud model reasoning and other methods. There are many research results on sorting algorithms, which are well known to those skilled in the art and will not be repeated here. For details, please refer to the fifth chapter of "Avionics Countermeasures Networking" published by National Defense Industry Press, written by Wang Xing and others, and Xi'an Electronics Co., Ltd. Wang Hua's master's thesis of the University of Science and Technology "Research on the Ranking Method of a Type of Target Threats in Situation Assessment" and other documents. After the judgment results of multiple algorithms are fused, the fusion algorithm may adopt a voting fusion fusion method, which is well known to those skilled in the art and will not be described again. The judgment result is output to the terminal module in the form of alarm information. The threat assessment algorithm library has the characteristics of modularity and scalability. Specifically, its modularity is reflected in the use of multiple threat assessment algorithms to assess the threat of the target. Each algorithm is a separate algorithm module, and the output results are formed after fusion. The integrated threat assessment results are output to the terminal module in the form of alarm information; its scalability is reflected in the fact that each threat assessment algorithm in the algorithm library can be run as a separate algorithm module, and modules can be added or deleted as needed. Extends the entire threat assessment algorithm library.

(4) Processing process of the threat data update module: The threat data update module receives the fusion identification result data in the back-end identification, and according to the update criterion of "recurrence and repeated confirmation", when the number of repeated occurrences of a certain radiation source data reaches the set value After K times are determined, this radiation source parameter is written into the threat database in the front-end identification in the front-end alarm module to realize the online update of the threat database.

According to the above data processing flow, on the basis of Fig. 5, Fig. 6 shows the data processing architecture of the airborne radar warning device using the front-end and back-end parallel processing mechanism, and further shows the internal structure of each module in Fig. 5, reflecting the back-end division The algorithm modular structure of selection, back-end identification, and back-end threat assessment, as well as the cross-linking of the alarm device with the airborne radar, the data link end machine, and the IFF through the airborne bus.

Compared with the existing airborne radar warning device data processing method, the present invention has the following characteristics and advantages in 9 aspects:

1. Adopt the "front-end and back-end" parallel alarm mechanism, which has both rapid alarm and accurate alarm capabilities. The invention adopts the parallel processing mechanism of front and back ends, wherein the front end runs a fast alarm algorithm to realize the rapid sorting, identification and alarm of the detected signal data, and the back end runs an accurate alarm algorithm to realize the secondary accurate sorting of the detected signal. , identification and warning. However, the existing equipment only has the front-end alarm capability of the present invention, and can only realize rapid alarm.

2. Modular and extensible. The sorting and identification algorithm of the existing equipment adopts a one-time embedding method, which cannot be deleted, replaced, expanded and upgraded. The back-end alarm processing of the present invention adopts a modular design, and the sorting algorithm library, the identification algorithm library and the threat assessment algorithm library are respectively composed of a plurality of sorting, identification and threat assessment algorithm modules. Various sorting and identification algorithms participate in the processing of detected signal data in the form of algorithm modules. Each algorithm module runs independently, and the operation result supports further fusion judgment. At the same time, the algorithm module supports deletion, replacement, expansion and upgrade.

3. Higher accuracy. The existing equipment adopts a fast sorting and identification algorithm for sorting and identification. Since the adopted algorithm is single and only processes the detected data once, the accuracy is not high. The back-end alarm processing of the present invention uses multiple sorting and identification algorithm modules to finely sort and accurately identify the detected data, and can also make fusion judgments based on the sorting and identification results of different algorithm modules, which greatly improves the alarm processing results. confidence and accuracy.

4. IF information processing capability. The sorting and identification algorithm of the existing equipment receives full pulse parameter information for data processing, including pulse amplitude, pulse width, carrier frequency, pulse arrival time and pulse arrival angle. The front-end alarm of the present invention is mainly based on the data processing architecture in the existing equipment, but a back-end alarm processing part is added. The back-end alarm part can receive full pulse parameter information and intermediate frequency signal data, and extract more intermediate frequency features based on the intermediate frequency signal data. On this basis, multiple sorting and identification algorithm modules are used to finely sort and accurately identify the detected data.

5. Online update of threat database. The threat database of the existing equipment is loaded before executing the task, and it does not support real-time and dynamic update of the threat database during the execution of the task, and does not have the ability to learn knowledge. The back-end alarm processing of the present invention can record the radar radiation source data that occurs repeatedly during the task execution process, and supplementally record the radar data into the threat database, so as to realize the online update of the database, and have certain knowledge learning ability.

6. Multi-algorithm module result fusion. The sorting, identification and threat assessment of existing equipment only relies on the processing of a single algorithm, and the accuracy and confidence are not high. After the algorithm modules in the sorting, identification and threat assessment algorithm library in the back-end alarm processing proposed by the present invention operate independently, the processing results of multiple algorithm modules are fused and judged, which can realize the mutual verification of the processing results of each module, and improve the Confidence and accuracy of the results.

7. Multi-sensor data fusion. The data processing of the existing equipment only relies on the data detected by the airborne radar alarm itself for sorting and identification. The back-end alarm processing of the present invention is helpful to accurately identify the type, orientation and working state of the radar radiation source by introducing other airborne sensor data and information fusion with the airborne radar alarm device's own data, and improving the accuracy of identification .

8. Data utilization is high. The existing equipment adopts a fast sorting algorithm for sorting and identification. Since the sorting algorithm is single and only processes the detected data once, the data utilization rate is not high, and a large amount of data is not fully processed. The front-end alarm processing of the present invention adopts a fast sorting and identification algorithm to realize rapid alarm, focusing on the real-time nature of the alarm processing, and the back-end alarm processing adopts a plurality of sorting and identification algorithm modules to perform refined processing on the detected radar signals, thereby reducing the timeliness. requirements, focusing on the accuracy of alarm processing and higher data utilization.

9. It has strong environmental adaptability and can handle massive and intensive detection data. Although the existing equipment has adopted fast algorithms to quickly sort, identify and alarm the detected data, it is still difficult to adapt to the increasingly dense data flow. The front end of the present invention follows the processing idea of the existing equipment, realizes rapid alarm, and focuses on real-time performance. In the back end, multiple algorithm modules are used to carry out refined alarm, and the detection data that is not sufficiently processed by the front end can be processed in a refined manner. Less demanding but more focused on accuracy. In particular, the data that is difficult to sort and identify in the front-end alarm can be processed by the algorithm in the back-end alarm part. Therefore, under this parallel processing mechanism, the airborne radar warning device is more adaptable to the complex and dense environment.

Claims (6)

1. a kind of airborne radar alarm device adopting front-end and back-end parallel processing mechanism, comprising antenna, receiving measurement module, data processing part module, terminal module, threat data update module; it is characterized in that Antennas for intercepting radar radiation source signals in space; The receiving measurement module converts the radio frequency or high frequency signal intercepted by the antenna into a digital signal, measures the frequency, arrival time, pulse width, angle of arrival, direction of arrival, intermediate frequency parameters and other parameter information of the signal, and forms a pulse parameter stream and outputs it ; The data processing module sorts the pulse parameter stream processed by the receiving measurement module, sorts the parameters of a single radiation source from the aliased pulse parameter stream, and performs template matching with the threat database to realize the detection of radar radiation sources. Identify, and then perform threat assessment according to the identification result, and output the result of the threat assessment to the terminal module; Terminal modules, which provide threat information to other devices/systems through video or audio information; The threat data update module, according to the radiation source data obtained from the accurate identification of the back-end alarm module, after a certain number of repeated occurrences is confirmed, it is written into the threat database to realize the update of the threat data. 2. a kind of airborne radar warning device data processing method utilizing the front-end and rear-end parallel processing mechanism of the airborne radar warning device according to claim 1, is characterized in that, the concrete process of data processing is as follows: (1) After the detected pulse flow is measured by the receiving measurement module, a pulse parameter flow is formed. The pulse parameter flow includes the full pulse parameter flow and the intermediate frequency data flow; the full pulse parameter flow and the intermediate frequency data flow are sent to the back-end alarm module. The front-end alarm module only receives the full pulse parameter stream; (2) The processing process of the front-end alarm module: (a) Perform front-end sorting on the full pulse parameter stream; continue to perform front-end identification on the data that is successfully sorted, and send the data that is not successfully sorted into the back-end alarm module for back-end sorting, and further fine-tune sorting; (b) Perform front-end identification on the successful sorting data; match the radar radiation source information in the threat database according to the sorting parameters, and if the matching is successful, perform front-end threat assessment on the successfully matched data, that is, perform threat level calculation and sorting, and match Unsuccessful data is sent to the back-end identification of the back-end alarm module for accurate identification; (c) Perform front-end threat assessment on the matching successful data, and output the judgment result to the terminal module in the form of alarm information; (3) The processing process of the back-end alarm module: The back-end alarm module has a modular and scalable back-end sorting algorithm library, back-end identification algorithm library and threat assessment algorithm library; (a) Use the algorithm in the back-end sorting algorithm library to perform back-end sorting on the full-pulse parameter stream, the intermediate frequency data stream, and the unsorted data; Select the fusion result data to continue the back-end identification, and use the back-end identification algorithm library to carry out the back-end identification. In this process, the data that is not successfully sorted is filtered out as clutter data; (b) There are three sources of processing data for back-end identification: data of unsuccessful front-end identification, data of sorting and fusion results, and airborne bus data from airborne radar, IFF, and data link terminal; The obtained identification fusion result data is sent to the back-end threat assessment, and the threat assessment algorithm library is used for threat determination, and the identification fusion result data is sent to the threat data update module for storage; (c) using multiple threat assessment algorithms to perform back-end threat assessment on the identification fusion result data; after the judgment results of multiple algorithms are fused, a fused threat assessment result is formed, which is output to the terminal module in the form of alarm information; (4) Processing process of the threat data update module: The threat data update module receives the identification and fusion result data, and according to the update criterion of "recurrence and repeated confirmation", when the number of repeated occurrences of a certain radiation source data reaches the set K times Then, the radiation source parameter is written into the threat database in the front-end identification in the front-end alarm module to realize the online update of the threat database. 3 . The data processing method for an airborne radar alarm device according to claim 2 , wherein the front-end alarm and the back-end alarm are processed in parallel, and the tasks of sorting, identification and threat assessment are performed in parallel at the front-end and the back-end. 4 . 4. The method for processing airborne radar alarm device data as claimed in claim 2, wherein the front end adopts the sorting identification and threat assessment algorithm of the existing airborne radar alarm device to ensure the real-time performance of the alarm, and the back end adopts a module It can reduce the real-time requirements and improve the accuracy of alarms. 5. The data processing method for an airborne radar alarm device according to claim 2, wherein the back-end sorting, back-end identification and back-end threat assessment processing in the back-end alarm processing all adopt modular and extensible methods. Algorithm library, and the fusion of multiple algorithm processing results; specifically, its modularity is reflected in the use of multiple algorithm modules for independent and parallel sorting, identification and threat assessment tasks, each algorithm is a separate algorithm module, and the output The results are fused to form a fusion result of sorting, identification and threat assessment; its scalability is reflected in the fact that each algorithm in the algorithm library can be run as a separate algorithm module, and the algorithm modules can be added or deleted as needed. The expansion of the entire identification algorithm library is realized; its fusion is reflected in the independent operation and calculation of the algorithm modules in the sorting, identification and threat assessment algorithm library, and the processing results of multiple algorithm modules are fused and judged, so as to realize the mutual interaction of the processing results of each module. confirmed. 6. The method for processing airborne radar warning device data according to claim 2, wherein in the back-end identification processing in the back-end alarm, other airborne sensor data is introduced, and information is carried out with the data of the airborne radar warning device itself. fusion.

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