A new particle filter tracking algorithm based on Rayleigh distribution

The particle filter is a nonlinear filtering algorithm and it is widely used in target tracking. In the basic particle filter, the particles are scattered by Gaussian distributions, and the target for low-speed movement and gentle changes can be better captured. However, when the motion status of target suddenly changed, such as sudden acceleration, deceleration, or turning, etc., it often leads to the target loss. The reason is that the tailing of the Gaussian distribution curve is relatively lighter than that of the Rayleigh distribution, and then it causes the distributing range of particles is too small to capture the target. Considering this issue, the Rayleigh distribution is proposed to spread the particles, and then achieve the particles reproduction and dissemination, the Rayleigh distribution parameters is adaptively adjusted according to the rate of movement of the target, and through the secondary particle filter method to improve tracking accuracy. The experiments demonstrate that the particle propagation mechanism based on Rayleigh distribution can effectively enhance the ability of capturing target.