基于改进SFLA-PF算法的OFDM系统的目标跟踪

在OFDM通信系统中,为了解决非线性的目标跟踪问题,提出了基于改进混合蛙跳算法(SFLA)和粒子滤波算法(PF)相结合的方法来研究动态目标跟踪技术.首先利用高斯变异的局部搜索能力强和柯西变异的全局搜索能力强等优点对混合蛙跳算法进行改进,然后用改进后的混合蛙跳算法来优化粒子滤波算法进行动态跟踪,其优点不需要重采样步骤,有效地保持了粒子的多样性和有效性.仿真结果表明,该算法能够有效实现动态目标跟踪,并且跟踪效果优于同等条件下的混合蛙跳算法和粒子滤波算法.

Improved tracking targets SFLA-PF algorithm based on OFDM system

In the OFDM communication system, in order to solve nonlinear target tracking problem, we propose an improved SFLA (SFLA) and particle filter (PF) based on a combination of methods to study the dynamic target tracking technology. Firstly, Gaussian mutation local search ability and Cauchy mutation global search ability, etc. for SFLA improved, then SFLA improved particle filter algorithm to optimize the dynamic tracking, the advantage of not requiring resamplingSsteps to effectively maintain the diversity and effectiveness of the particles. The simulation results show that the algorithm can effectively achieve dynamic target tracking,and tracking better than SFLA and particle filter algorithm under the same conditions.