磷虾群免疫粒子滤波的机载单站无源定位算法

Airborne Single Observer Passive Location Based on Krill Herd Immune Particle Filter

为了进一步提高机载单站无源定位的精度,将磷虾群优化思想引入到粒子滤波的重采样阶段,提出了一种磷虾群免疫粒子滤波算法。该算法利用磷虾的受诱导运动、觅食以及随机扩散行为,将粒子导向高似然区域,有效缓解了粒子退化问题。同时,其采用了人工免疫算法的变异操作,避免了早熟现象的出现,提高了粒子的多样性,克服了粒子贫化问题。仿真结果表明,新算法改善了机载单站无源定位的定位精度以及收敛速度。

In order to improve the positioning accuracy of airborne single observer passive location,a novel particle filter based on krill herd immune algorithm is proposed,while the krill herd optimization method is introduced into the resampling process. The particles are moved to the high likelihood area, through the induced motion,foraging movement and random diffusion behaviors. Then the effect of the degeneracy problem is reduced. Meanwhile,the mutation operation of the artificial immune algorithm is adopted to avoid the premature phenomenon. The diversity of the particles is improved,and the impoverishment problem is solved. Simulation results indicated that the novel algorithm improve the performance of the positioning accuracy and convergence velocity.