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Antenna deployment method for multistatic radar in dynamic environment

机译:动态环境下多基地雷达的天线部署方法

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摘要

In this paper, considering multiple surveillance regions in a dynamic environment, we investigate an optimal antenna deployment problem for distributed multistatic radar. The problem is solved by proposing a prediction based particle swarm optimization (PBPSO) algorithm. Unlike the traditional particle swarm optimization (PSO) method, which needs completely recomputation when the environment changes, the proposed method uses the information about the previous optimal deployment schemes to predict and optimize the current one. So it greatly increases the solving efficiency and computational load of the optimal problem. Firstly, by dividing a continuous time period into several scenarios, we use the previous optimal scheme and a Kalman prediction model to predict an approximate optimal scheme for the current scenario. Then, to obtain the real optimal scheme, we can use the predicted optimal scheme and PSO method to optimize. Numerical results are provided to verify the advantages of PBPSO in optimizing the antenna deployment scheme in a dynamic environment.
机译:在本文中,考虑到动态环境中的多个监视区域,我们研究了分布式多基地雷达的最佳天线部署问题。通过提出基于预测的粒子群优化(PBPSO)算法解决了该问题。与环境变化时需要完全重新计算的传统粒子群优化(PSO)方法不同,该方法使用有关先前最佳部署方案的信息来预测和优化当前方案。因此,极大地提高了最优问题的求解效率和计算量。首先,通过将连续的时间段划分为多个方案,我们使用先前的最优方案和卡尔曼预测模型来预测当前方案的近似最优方案。然后,要获得实际的最优方案,我们可以使用预测的最优方案和PSO方法进行优化。提供了数值结果,以验证PBPSO在动态环境中优化天线部署方案方面的优势。

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