摘要
针对由于积累时间长、目标距离徙动和频率徙动导致相参积累效能降低的问题,提出了一种基于多种群的粒子群优化算法。首先将目标回波数据进行分段,使得段内目标回波数据分布不会跨距离单元和频率单元,然后利用基于种群交换的多种群粒子群优化算法进行距离、速度和加速度参数搜索,采用迭代寻找全局最优粒子,作为目标的距离、速度和加速度,实现目标回波的相参积累。仿真试验验证了算法的有效性。
Due to the long accumulation time,the target range migration and frequency migration result in the reduction of the coherent accumulation efficiency.A particle swarm optimization(PSO)algorithm based on multiple swarms is proposed.First,the target echo data is segmented so that the data in the segment does not cross the distance and frequency unit.Then,the multiple swarms particle swarm optimization algorithm based on population exchange is used to search for distance,velocity and acceleration parameters.The global optimal particles are found by iteration,which are used as the distance,velocity and acceleration of the target to achieve the coherent accumulation of the target echoes.Simulation experiments show the effectiveness of the algorithm.
作者
杨娜
刘爱华
易堃
占凯
王阳阳
YANG Na;LIU Aihua;YI Kun;ZHAN Kai;WANG Yangyang(Shanghai Radio Equipment Research Institute,Shanghai 201109,China)
出处
《制导与引信》
2022年第1期1-4,28,共5页
Guidance & Fuze
关键词
长时间积累
弱信号检测
种群交换
速度权值
long time accumulation
weak signal detection
population exchange
speed weight
