Sequential Smoothing and Filtering for Maneuvering Target Tracking

Measurement concatenation is a general formulation which allows rapidly sampled measurements to be batched and utilized at the slower algorithmic processing rate. It was shown in [Cloutier et al., 1991a] how sequential smoothing and filtering can be carried out within the measurement concatenation structure; a smoothing and filtering algorithm (SFA) was then developed based on a maneuvering target model. This paper addresses performance enhancement during the quiescent periods by combining a nonmaneuver model-based SFA and a maneuver model-bsed SFA. The paper also investigates the SFA in terms of algorithm comparison and design parameter tuning.