基于粒子滤波参数估计的混沌保密通信系统

Chaotic secure communication based on parameter estimation of a particle filter

针对混沌参数调制保密通信系统中扩展卡尔曼滤波算法和无味卡尔曼滤波算法对混沌系统的状态和参数估计性能较差的问题,提出了用粒子滤波算法估计混沌系统参数的方法。在系统的发送端,通过待发送的二进制符号调制混沌系统的参数进而产生混沌信号。在接收端,粒子滤波器用接收到的混沌信号估计出相应的混沌系统参数,从而恢复出发送端的二进制符号。仿真结果表明,较扩展卡尔曼滤波和无味卡尔曼滤波,粒子滤波算法在估计混沌系统参数时具有更短的收敛时间和更小的估计误差,能更有效地实现混沌保密通信。

The extended Kalman filter algorithm and unscented Kalman filter algorithm have bad estimation performance of the chaotic system state and parameter in secure communication based on chaotic parameter modulation.To solve this problem,the particle filter algorithm was used to estimate the state and parameter.The binary symbols sent were used to modulate the parameters of chaotic systems in the transmitter.The corresponding parameters of chaotic systems were estimated through a particle filter with a received signal in the receiver.Simulations show that in comparison with the extended Kalman filter and unscented Kalman filter,the particle filter algorithm in chaotic parameter estimation has shorter convergence time and lower estimation error,and secure communication can be more effectively realized.