基于DSP的改进粒子滤波算法研究

介绍了粒子滤波基本原理,针对粒子滤波计算量大和难以用硬件实现等缺点对粒子滤波算法进行了改进,使其平均计算周期缩短为原来的90%,应用DSP实现了粒子滤波算法。改进粒子滤波算法主要优化了原粒子滤波算法中权值计算、重采样和输出步骤,使其计算速度和滤波精度有所提高。这种改进粒子滤波算法在DSP系统中进行仿真,结果证明它具有速度快,精度高的优点。

Improved Particle Filter Algorithm Based on DSP

Particle filter is based on the Monte Carlo and recursive Bayesian estimation which has special advantages in dealing with the nonlinear and non-Gaussian problems. However, both the enormous computations and low speed restrict its implementation in real-time system. At first, the basic theory of particle filter is introduced. Then, the particle filter algo- rithm is improved for solving the disadvantages of enormous computations and hard implementation of hardware, which reduced the average cycle to 90%. At last, particle filter algorithm is fulfilled through DSP. Compared with original particle filter algorithm, the improved algorithm optimizes the steps of computation of weights, resample and output, which improve the calculator speed and filter precision. The improved particle filter algorithm testifies its advantages of fast speed and high accuracy through carrying out simulation in DSP system.