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Research On Jamming Resource Assignment For Cooperative Jamming With Multi-ECAVs

Posted on:2014-03-11Degree:MasterType:Thesis
Country:ChinaCandidate:M Y LiFull Text:PDF
GTID:2272330479479244Subject:Control Science and Engineering
Abstract/Summary:PDF Full Text Request
The research on jamming resource assignment for cooperative jamming with multi-ECAVs has important practical significance for improving the operational effectiveness of combat aircraft and battlefield survival. In recent years, due to the appearance of a variety of modern, high-performance anti-aircraft weapons, making the task of aircraft penetration more and more difficult, dangerous and intensity. In this context, the task of cooperative jamming with multi-ECAVs facing more complex environment, making the optimization solution process of the problem is very difficult. Therefore, this paper mainly studies the following issues:1. Analyzed and modeled the optimization problem of jamming resource assignment for cooperative jamming with multi-ECAVs. Through analysis the complex task environment that cooperative jamming with multi-ECAVs facing, established the threat assessment model based on fuzzy discrete dynamic Bayesian network which can handle continuous observations with qualitative reasoning; Secondly, it analysis the performance parameters of the ECAVs and radars, selected radar jamming effect factors and indicators from both offensive and defensive, and design a jamming effect assessment model comprehensive multi-attribute decision making method and fuzzy set theory based on the fuzzy uncertainly of the indicators to jamming effect which can assess the effect on radar jamming reasonably and quickly; Finally, established the multiple constrained optimization model for solving the problem of jamming resource assignment for cooperative jamming with multi-ECAVs which laid below the base basis.2. Studied the assignment methods of cooperative jamming based on dynamic programming. The problem of jamming resource assignment for cooperative jamming with multi-ECAVs problem is a high-dimensional, multi-constrained combinatorial optimization problem, the general idea is to use optimization methods to solve the problem. This article gave detailed description of the basic concepts and principles of dynamic programming algorithm, deduced the order recursive equations for solving the optimization problem of jamming resource assignment for cooperative jamming with multi-ECAVs. Then aimed at the specific problem of jamming resource assignment for cooperative jamming with multi-ECAVs, gave the solution process of dynamic programming algorithm. Finally, gave an example of effectiveness and performance of the algorithm for verification and analysis.3. Designed the optimization solution method of jamming resource assignment for cooperative jamming with multi-ECAVs based on the fusion algorithm which comprehensive Ant Colony Algorithm(ACA) and Partial Swarm Optimization Algorithm(PSO). Aimed at the shortcomings of dimensional disaster in the solution process of cooperative jamming resource assignment problem with optimization method, now to solve the problem with intelligent optimization methods. Introduced the solution process of cooperative jamming resource assignment based on ACA, and analyzed the deficiencies of this algorithm in the solution process; For the lack of initial pheromone and slowly and blindness deficiencies in the search process, a fusion algorithm which comprehensive ACA and PSO is designed. This fusion algorithm finding the current global optimal solution by using the speed and global characteristics of PSO, adjusting the initial pheromone of ACA based on the current global optimal solution, and then obtaining the global optimal solution by making use of the positive feedback mechanisms of ACA; Finally, validated the effectiveness and performance of the algorithm with simulation.
Keywords/Search Tags:cooperative jamming, source assignment, threat assessment, fuzzy discrete dynamic Bayesian network, radar jamming assessment, ACA, PSO
PDF Full Text Request
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