Memoryless Polynomial RLS Adaptive Filter for Trajectory Target Tracking

In order to find an effective solution to trajectory target tracking, a memoryless polynomial adaptive filter is proposed in this paper. Unlike Volterra adaptive filter, the proposed memoryless polynomial filter is composed of different monomials, which can fit orbit trajectory very well. Besides, the memoryless polynomial filter can be separated into a linearization filter and a transversal filter. Analogous to linear RLS adaptive filter, a RLS adaptive filter is derived from the memoryless polynomial filter, called Memoryless polynomial RLS adaptive filter (MLPRLS adaptive filter). Experiments show that the proposed filters have better performance than that of normal RLS filters in trajectory tracking.