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With the rapid development of electronics industry measurement technology and electronic measuring instruments technology, radar network technology has became the important measure of radar’s anti-jamming, anti-radiation missile, anti-stealth aircraft, and low attitude attack. Because of the using of radar network systems, there is a full-scale action system, it has the abilities of multi-frequency, multi-ways of work, multi-overlap coefficient, and strengthens the communication and security of information. So it could exert the strongpoint of system counterwork and colony counterwork sufficiently, and be a huge challenge of the traditional jamming ways.The first work of this paper is to introduce and analyzes the“four counteractions”, also introduce the advantages of radar network, better than the single radar, then got the principle of radar network system. This principle including detection probability, similar frequency jamming, airspace cover redundancy, resources utilize and low attitude repair. It represents the effect of radar network.Secondly, introduce several typical radar network system deployments; deduce a probability of target detection models for Radar network system under multi-radars deployments. This model can simulate the radar detection area effectively. Using Monte Carlo method to solve the problem and simulate in the serious typical radar network deployments. Obtain the rational planning for deploy the radar to meet the strategic requirements in a actual position environment, determine what to do next.Thirdly, according to the radar network deployment is a multi-objective optimization, and a host of intractable combinatorial optimization problems, established an optimal deployment based on Radar Network fixed position, descript of the problem Radar network elements in detail. Using intelligent type and parallelism of Genetic algorithm to solve the problem and simulate. In the condition of given resources, gain a rational radar network system strategic deployment.Finally, this paper established a coverage factor of the airspace detection area to radar network model; discuss brief radar network constraints at the actual positions in the environment. Adopt mixed culture and genetic algorithm, the model data test simulation. And then, the solving process of the algorithm for this optimization problem is discussed. The results show that the algorithms can effectively guide the search, greatly reduces the solution space of the optimization and improve the efficiency of optimal deployment of a network. Radar Network and get the maximum detection region, to satisfy the actual environment constraints, which is very valuable for optimizing the deployment of radar networks.
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