CN109357696B - Multi-source sensor information fusion closed-loop testing framework - Google Patents
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Abstract
The invention provides a multi-source sensor information fusion closed-loop test framework, and aims to provide a closed-loop test framework which is high in test efficiency and flexible in test case. The invention is realized by the following technical scheme: in the dynamic test process based on the scene, the sensor detection model sends target detection information generated in real time to an information fusion system for information fusion processing; the information fusion system decomposes the evaluation index of the information fusion performance of the sensor into a series of influencing elements, establishes the mapping relation between the index and the elements, sends the fusion information of the target output through target association and track prediction into an analysis evaluation module for real-time analysis and evaluation, dynamically adjusts the scene situation and the test case of the scene in real time according to the index result, automatically generates a new test strategy, automatically searches for the inferior, automatically searches for the boundary and the adaptability of the fusion algorithm, automatically generates a real-time plan containing the aircraft track, and can realize the test case with the dynamic change of the test scene.
Description
Technical Field
The invention relates to a closed loop dynamic test framework mainly aiming at information fusion of an airborne multi-source sensor.
Background
Early data fusion has the information sources of multiple sensors of the same type, such as multiple sonars, multiple radars, multiple passive detection target positioning and the like, and the information form of the data fusion is mainly sensor data. The information fusion technology enables the joint detection and cooperative tracking of targets by multiple sensors, which is important for finding weak signal targets as early as possible. Information fusion refers to the integration and processing of information in multiple carriers to achieve a certain purpose. Information fusion is also called data fusion (data fusion), and an important function of information fusion is feedback control of information sensing and collecting equipment and a fusion process. The feedback control comprises control of cooperative work of information sources, control of a sensor detection working mode, target detection parameter control, parameter control of fusion judgment (such as association judgment, target maneuvering judgment and the like), multivariate parameter control in situation and threat estimation and the like. The information fusion technology has considerable complexity and difficulty, and the complexity is expressed in that: intentional interference or damage can cause the monitoring data of the sensor network to be incomplete, inaccurate and even mutually exclusive; from the perspective of information, the information fusion is analyzed in the hierarchy, and the information fusion can be divided into three levels: a data level, a feature level, and a decision level. The data level fusion is the fusion of the lowest level, directly carries out fusion processing on the sensor original observation data which is not preprocessed, and then carries out feature extraction and decision based on the fused result. The method has the advantages that the method only has less data loss, keeps as much as possible fine information, and has the highest precision; the disadvantages are that the sensor data that needs to be processed is too much, the processing time is long, the real-time is poor, and only the data of homogeneous sensors can be processed. The feature level fusion belongs to the fusion of middle layers, and is based on the fusion of feature vectors after the sensors are subjected to preliminary preprocessing and basic feature vectors are abstractly extracted by each sensor. The method has the advantages that not only enough amount of important information is kept, but also effective data compression is realized, the requirement on bandwidth is reduced, and the real-time performance and the anti-interference capability of the processing process are improved. But the performance of the fusion system is reduced due to the inevitable loss of part of the information. The decision-level fusion is a high-level fusion, firstly, each sensor makes a decision based on the data acquired by the sensor, and then fusion processing is carried out according to a certain criterion on the basis to obtain a final decision. Its advantages are less dependence on sensor, fused information of heterogeneous sensors, low requirement on bandwidth and high anti-interference power. But with the greatest amount of data loss and relatively the lowest accuracy. Some scholars integrate the existing technology and aim to establish a general information fusion framework, and hope that the general information fusion framework can be applied to various information fusion systems as much as possible. However, no complete theoretical framework and fusion model have been formed yet, and currently used multi-sensor information functional models include a Dasarathy functional model (a very useful classification for data fusion, which is defined according to the type of processed data or information and the type obtained by processing), a joint command laboratory (JDLJointDirectors laboratories) model logically divides the information fusion function, which includes some function definitions of any information fusion system, has a closed loop to control the flow of information, and logically divides the information fusion function into an Omnibus functional model and the like, but all of which have more or less defects and cannot be generalized And synthesizing and applying to obtain the consistency explanation and description of the measured object, thereby realizing corresponding decision and estimation. Although much research has been done on multi-sensory information fusion, there is not yet a generalized, efficient fusion algorithm. The multisource information fusion is that multisensor information resources in different time and space are fully utilized, and computer technology is adopted to automatically analyze, synthesize and control multisensor observation information obtained according to time sequence under a certain criterion to obtain consistency explanation and description of a measured object so as to complete required tasks. The sensing information fusion is a form framework for integrating sensing data by using a mathematical method and a processing technology, multi-source information needs to be comprehensively processed for obtaining useful information, and a specific process is complex. In the application of information fusion, expert knowledge is mainly modeled through rules connected with features. Multisensor information fusion (multisensorinformation) or multisource information fusion (multisourceinformation). Since early fusion method research was directed to data processing, information fusion is sometimes referred to as data fusion (data fusion). According to different data processing methods, the architecture of the information fusion system has three types: distributed, centralized, and hybrid. Distributed: the method comprises the steps of firstly carrying out local processing on original data obtained by each independent sensor, and then sending results to an information fusion center for intelligent optimization and combination to obtain final results. The distributed system has low requirement on communication bandwidth, high calculation speed, good reliability and continuity, but the tracking precision is far from centralized; the distributed fusion structure can be further divided into a distributed fusion structure with feedback and a distributed fusion structure without feedback. Centralized type: the original data obtained by each sensor is sent to the central processing unit directly in a centralized manner for fusion processing, so that real-time fusion can be realized, the precision of data processing is high, the algorithm is flexible, and the defects are that the requirement on the processor is high, the reliability is low, the data volume is large, and the realization is difficult; mixing: in the hybrid multi-sensor information fusion framework, part of sensors adopt a centralized fusion mode, and the rest of sensors adopt a distributed fusion mode. The hybrid fusion framework has strong adaptability, gives consideration to the advantages of centralized fusion and distributed fusion, and has strong stability. The structure of the hybrid fusion mode is more complex than the structures of the first two fusion modes, so that the communication and calculation costs are increased. What is indispensable in information fusion is a mathematical tool that efficiently describes all input data in a common space, while properly integrating the data, and finally outputting and representing the data in a proper form. The multi-source information fusion mainly refers to the comprehensive analysis and processing of multi-sensor information by using a computer, so that the understanding of the essence of objective objects is obtained, and the process has complexity along with the diversity of the essence of the objective objects. The multi-source information fusion is an emerging data processing technology, and is characterized in that a computer technology is utilized to automatically analyze and comprehensively process measurement information from multiple sensors or multiple sources according to a time sequence and a certain criterion so as to complete needed decision and judgment.
Due to the complexity of the aircraft engine, the types and the number of the sensors are increased sharply, a plurality of sensors form a sensor array, the acquired original information is often disordered, scattered or even wrong, and valuable decision information can be obtained only by fusing a large amount of information. The condition of the detected target object is detected in real time through the sensor, and the detected target object and other data sources jointly form information input of the data fusion system. When the data are fused and processed and do not meet the expected performance indexes, the resource allocation of the sensors can be adjusted by adding a sensor management system, so that the whole fusion process becomes a closed loop structure, the difference between the current fusion result and the expected performance is utilized, the sensor management strategy is further adjusted, the fusion result is close to the expected performance, the expected performance requirements can be met, the waste of sensor resources is avoided, and the sensors are fully utilized.
The selection of the test method directly influences the complexity, fusion quality and performance of the evaluation fusion processing logic. In addition, from the perspective of engineering development, a reasonable information fusion test scheme is a necessary condition for ensuring the robustness of the fusion algorithm in examination, and scientific test and evaluation examination on information fusion in a scheme demonstration stage and a design stage are advocated, so that manpower and material resources can be saved, and the quality of engineering development can be ensured. However, most of the current implementation schemes of the information fusion test method focus on aspects of static test flight data playback, dynamic scene driven open-loop test and the like. Due to the characteristics of the sensor and uncertainty of the working environment, the sensor data contains uncertain components, so that the authenticity or numerical description of the objective object cannot give an explicit judgment. Compared with a single threshold judgment hard judgment sensor, the method adopts multi-threshold or variable threshold to judge noise and clutter on the original measurement signal, and the detection result depends on judgment conditions (such as false alarm probability, detection probability or conversion reliability) to realize the detection and tracking of weak signal targets or maneuvering targets. The real test flight data playback excitation test and the virtual dynamic flight data excitation test based on the scene can be realized. However, from the application effect, the existing information fusion test method has many disadvantages, mainly including:
1. test scenarios and case scripts are rigid. In the existing test scenes and cases, designers design a plurality of typical test scenes in a targeted manner according to fusion indexes to be evaluated before testing, instantiate the plurality of scenes into test cases, and then test and evaluate the test cases one by one. In general, a typical test case can only perform a single item of test, and the test process is uniform and has low flexibility.
2. Test scenarios and use cases are numerous. As described above, for different evaluation items, there are hundreds of cases in a typical test scenario, and each case needs to perform the whole test flow, which greatly wastes human resources.
3. The evaluation result is independent of the test case. The test case cannot be generated according to the evaluation result, and the test case is usually ready to be implemented, rather than being generated in a targeted manner according to the evaluation result.
Disclosure of Invention
Aiming at the defects of the existing multisource information fusion test method for the aircraft navigation airborne sensor, the invention provides a multisource sensor information fusion closed-loop test framework which has high test efficiency, can improve the relevance between a test case and an evaluation index and has flexibility.
The above object of the present invention can be achieved by the following measures, wherein the multi-source sensor information fusion closed-loop test architecture comprises: the system comprises a sensor detection model, an information fusion system, an analysis and evaluation module, a test strategy generation module and a test database, wherein the sensor detection model is arranged in a dynamic scene excitation module, the information fusion system is used as a test object, and the analysis and evaluation module, the test strategy generation module and the test database are characterized in that in the scene-based dynamic test process, the sensor detection model sends target detection information generated in real time to the information fusion system for information fusion processing according to aircraft flight path planning and six-degree-of-freedom information provided by a test strategy generation module test strategy and sensor parameter setting; in the information fusion testing stage, the information fusion system decomposes the evaluation index of the information fusion performance of the sensor into a series of influence elements in advance according to the information characteristics of task requirements and situation types, establishes a mapping relation between the index and the elements according to the influence elements, and sends the fusion information of the target output through target association and track prediction to an analysis evaluation module; the analysis and evaluation module carries out real-time analysis and evaluation on the received fusion information data, outputs analysis and evaluation information index data, and carries out observation, index correlation influence analysis and logic error searching through the test strategy generation module, dynamically adjusts the scene situation and the test case of the scene in real time according to the index result, automatically generates a new test strategy containing new aircraft track planning and new sensor parameters, feeds the test strategy back to the dynamic scene excitation module in a closed loop manner to carry out new case test, automatically searches for the inferior quality according to the information fusion evaluation result, automatically searches for the fusion algorithm boundary and adaptability, automatically generates the real-time planning containing the aircraft track, and can realize the test case with dynamically changed test scene.
Compared with the prior art, the invention has the following beneficial effects:
the testing efficiency is high. In the dynamic test process based on the scene, the sensor detection model generates the aircraft flight path planning and the six-degree-of-freedom information provided by the test strategy of the module according to the test strategy, and sensor parameter setting, sending the target detection information generated in real time to an information fusion system for information fusion processing, analyzing and evaluating observability of indexes by utilizing airplane multi-source information fusion, automatically generating a test strategy according to the mapping relation between the evaluation index and the influence elements thereof, realizing a closed-loop dynamic test framework of multi-source information fusion, completing an automatic inferior searching process, the complexity of the whole test process is reduced on the basis of automatically generating the test cases, the system test efficiency is improved, the corresponding test cases can be automatically generated according to the information fusion evaluation result, the test efficiency of information fusion is improved, and the boundary and the adaptability of the fusion algorithm can be automatically searched based on the performance of the information fusion. The fusion algorithm enables the fusion information to be higher in precision than any single information source, and the credibility of the target information can be greatly improved through fusion of the uncertain information.
The relevance of the test case and the evaluation index is improved. In the information fusion testing stage, the evaluation index of the information fusion performance is decomposed into a series of influence elements in advance according to task requirements, situation types, information characteristics and the like, establishing a mapping relation between indexes and elements according to the influence elements, sending the fusion information of the target output through target association and track prediction to an analysis and evaluation module, changing the test difficulty based on a strategy, achieving the boundary of evaluation and fusion performance, enhancing the association of test cases and evaluation indexes, by evaluating the performance index of the fusion algorithm in real time in the dynamic test process based on the scene and dynamically adjusting the scene situation in real time by adopting a strategy-based method according to the evaluation index result, the method is used for automatically evaluating the performance boundary of the fusion algorithm and automatically searching the logic errors of the fusion software, improves the relevance of the test case and the evaluation index, and lays a foundation for automatically generating the test strategy.
The test case has flexibility. The invention adopts the analysis and evaluation module to carry out real-time analysis and evaluation on the received fusion information data, outputs the analysis and evaluation information index data, observes the test strategy generation module, analyzes the index correlation influence, adjusts the test case of the scene in real time according to the index result, automatically generates a new test strategy containing new aircraft track planning and new sensor parameters, and automatically generates the test case containing the real-time planning of the aircraft track, thereby realizing the dynamic change of the test scene, changing the generated test case along with the change of the information fusion performance, realizing the dynamic change of the test scene, further achieving the purpose of long-time uninterrupted test, improving the continuity of the whole test process, and providing support for the robustness of the assessment information fusion algorithm. And the complex task environment can be dynamically generated, the flexibility of the test is greatly expanded, the flexibility of the test case is improved, the process of manually setting the test case is avoided, and the investment of human resources is reduced.
The dynamic test framework provided by the invention is an 'automatic inferior searching' process, reduces the complexity of the whole test process on the basis of automatically generating the test case in real time, improves the system test efficiency, enhances the relevance of the test case and the evaluation index, can dynamically generate a complex task environment, and greatly expands the test flexibility. But wide application has the multisensor information fusion of platforms such as man-machine and unmanned aerial vehicle.
Drawings
FIG. 1 is a schematic diagram of a testing principle of the multi-source sensor information fusion closed-loop testing architecture of the present invention.
The invention is further illustrated with reference to the following figures and examples.
Detailed Description
See fig. 1. In embodiments described below, a multi-source sensor information fusion closed-loop test architecture includes: the system comprises a sensor detection model arranged in a dynamic scene excitation module, an information fusion system used as a test object, an analysis and evaluation module, a test strategy generation module and a test database. The sensor adopts radar, UV chain, photoelectric detection and the like, and the initial state of the sensor model is a shutdown state. The information fusion system is used as a test object and is an engineering realization of a multi-source information fusion algorithm. The test database stores the detection information of the dynamic scene excitation module, the information fusion system information fusion information and the data output by the analysis and evaluation module in real time in the closed-loop test process, and provides data support for post analysis.
In the dynamic test process based on the scene, a sensor detection model sends target detection information generated in real time to an information fusion system for information fusion processing according to aircraft flight path planning, six-degree-of-freedom information and sensor parameter setting provided by a test strategy generation module test strategy; in the information fusion testing stage, the information fusion system decomposes the evaluation index of the information fusion performance of the sensor into a series of influence elements in advance according to the information characteristics of task requirements and situation types, establishes a mapping relation between the index and the elements according to the influence elements, and sends the fusion information of the target output through target association and track prediction to an analysis evaluation module; the analysis and evaluation module carries out real-time analysis and evaluation on the received fusion information data, outputs analysis and evaluation information index data, carries out observation and index association influence analysis through the test strategy generation module, searches for logic errors, adjusts a test case for dynamically adjusting scene situation and scene in real time according to index results, automatically generates a new test strategy containing new aircraft flight path planning and new sensor parameters, feeds the test strategy back to the dynamic scene excitation module in a closed loop manner to carry out new case test, automatically searches for inferior quality according to the information fusion evaluation results, automatically searches for fusion algorithm boundary and adaptability, automatically generates the real-time planning containing the aircraft flight path, and can realize the test case with dynamically changed test scene.
The dynamic scene excitation module is internally provided with dynamic scene excitation software which is used for controlling simulation operation, communication management, providing sensor model control operation, issuing sensor model parameters, acquiring flight platform data and the like. And loading and generating an initial platform motion track and a sensor parameter list of the test through built-in dynamic scene excitation software, and starting the test task.
And the dynamic scene excitation software transmits the target data output by the sensor model to the information fusion system to be tested and the analysis and evaluation software in real time. And the information fusion system to be tested performs fusion processing on the detection result of the sensor model and sends the processing result to the analysis and evaluation software.
And the analysis and evaluation module is internally provided with analysis and evaluation software, the analysis and evaluation software calculates evaluation indexes before and after fusion, and a calculation result is input into the self-adaptive test strategy generation software.
And the analysis evaluation module determines the evaluation index of the test according to the requirement of the fusion test, and the evaluation index of the test adopts the target track quality before and after fusion. If the test of this time aims at testing the target track under the high-speed maneuvering condition (such as the intensive flight of the target, the high-speed maneuvering flight of the target, etc.), the stable track output can still be kept after the fusion, and the evaluation indexes of this time are the stability of the target track and the number of the target tracks.
And the test strategy generation module generates a new test strategy according to the current evaluation index result and the test purpose through built-in self-adaptive test strategy generation software, and the test strategy adaptively corrects the current motion tracks of the two parties to generate a new platform motion track and a new sensor parameter setting list.
The self-adaptive test strategy generation software firstly generates an initial test strategy of the test, carries out motion track planning of the two parties according to the initial test strategy and generates a platform motion track and a sensor parameter initial setting list. And then dynamically adjusting the motion tracks of the two parties and the parameters of the sensors according to the test purpose and the real-time evaluation index result of the test in the test process. Examples are as follows:
the test purpose is as follows: the influence of different sensor usage combinations on the fusion result; and (3) testing strategies: the switching time sequence of each sensor is randomly and dynamically generated according to the action distance of each sensor, so that the use combination of the sensors is changed;
the test purpose is as follows: the influence of the decrease of the detection performance of the sensor on the fusion result;
and (3) testing strategies: according to the detection performance of each sensor, the motion characteristic of the target is dynamically changed, so that the target performs large-maneuvering flight, such as S-shaped flight, diving and pulling-up flight and the like, and the detection performance of the sensor is reduced.
The foregoing is merely a preferred embodiment of the invention, which is intended to be illustrative and not limiting. It will be understood by those skilled in the art that many variations, modifications, and even equivalents may be made thereto within the spirit and scope of the invention as defined in the claims, but all of which fall within the scope of the invention.
Claims (10)
1. A multi-source sensor information fusion closed-loop test architecture, comprising: the dynamic scene simulation system comprises a dynamic scene simulation module, an information fusion system, an analysis evaluation module, a test strategy generation module and a sensor detection model, wherein the dynamic scene simulation module, the information fusion system and the analysis evaluation module are respectively connected with a test database; in the information fusion testing stage, the sensor detection model sends target detection information generated in real time to the information fusion system for information fusion processing, the information fusion system decomposes the evaluation index of the information fusion performance of the sensor into a series of influence elements in advance according to the information characteristics of task requirements and situation types, a mapping relation between the index and the elements is established according to the influence elements, the fusion information of the target output through target association and flight path prediction is sent to an analysis evaluation module, the analysis evaluation module carries out real-time analysis and evaluation on the received fusion information data, the output analysis evaluation information index data is observed through a test strategy generation module, the index association influence analysis is carried out, logic errors are searched, a test case containing new aircraft flight path planning and new sensor parameters is automatically generated by dynamically adjusting a scene situation and a scene in real time according to index results, the test strategy is fed back to the dynamic scene excitation module in a closed loop mode to perform new case test, according to the information fusion evaluation result, the inferior is automatically searched, the boundary and the adaptability of the fusion algorithm are automatically searched, the real-time planning including the aircraft flight path is automatically generated, and the test case with the dynamically changed test scene can be realized.
2. The multi-source sensor information fusion closed-loop test architecture of claim 1, wherein: the test database stores the detection information of the dynamic scene excitation module, the fusion information of the information fusion system and the data output by the analysis and evaluation module in real time in the closed-loop test process, and provides data support for post analysis.
3. The multi-source sensor information fusion closed-loop test architecture of claim 1, wherein: the dynamic scene excitation module is internally provided with dynamic scene excitation software which is used for controlling simulation operation, communication management, providing a sensor detection model to control operation, issuing sensor model parameters and acquiring flight platform data, and an initial platform motion track and a sensor parameter list of the test are loaded and generated through the internal dynamic scene excitation software to start the test task.
4. The multi-source sensor information fusion closed-loop test architecture of claim 3, wherein: and the dynamic scene excitation software transmits the target detection information output by the sensor detection model to the information fusion system to be detected and the software of the analysis and evaluation module in real time.
5. The multi-source sensor information fusion closed-loop test architecture of claim 4, wherein: and the information fusion system to be tested performs fusion processing on the result of the target detection information of the sensor detection model and sends the processing result to the software of the analysis and evaluation module.
6. The multi-source sensor information fusion closed-loop test architecture of claim 1, wherein: and the analysis and evaluation module is internally provided with analysis and evaluation software, the analysis and evaluation software calculates evaluation indexes before and after fusion, and a calculation result is input into the self-adaptive test strategy generation software.
7. The multi-source sensor information fusion closed-loop test architecture of claim 1, wherein: the analysis evaluation module determines an evaluation index of the test according to the requirement of the fusion test, and the evaluation index of the test adopts the target track quality before and after fusion; the evaluation indexes of the test are the stability of the target track and the number of the target tracks.
8. The multi-source sensor information fusion closed-loop test architecture of claim 1, wherein: the test strategy generation module generates software through a built-in self-adaptive test strategy, the generation software generates a new test strategy according to the current evaluation index result and the test purpose, the test strategy adaptively corrects the current motion tracks of the two parties, and a new platform motion track and sensor parameter setting list is generated.
9. The multi-source sensor information fusion closed-loop test architecture of claim 1, wherein: the self-adaptive test strategy generation software firstly generates an initial test strategy of the test, carries out motion track planning of the two parties according to the initial test strategy and generates a platform motion track and a sensor parameter initial setting list.
10. The multi-source sensor information fusion closed-loop test architecture of claim 1, wherein: and the self-adaptive test strategy generation software dynamically adjusts the motion tracks of the two parties and the parameters of the sensors according to the test purpose and the real-time evaluation index result of the test in the test process.
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