Out-of-sequence track filtering using the decorrelated pseudo-measurement approach

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Abstract
Most practical multi-platform data fusion systems use the distributed tracking architecture where each sensor platform has its own local tracker. A local tracker performs tracking using measurements from one or more sensors and sends its track data to a central fusion system. When the track data from a local tracker is transmitted to the central fusion system using a communication network, the track data can arrive out-of-sequence due to random delays in the communication network and different processing times at local trackers. Track-to-track fusion using the equivalent decorrelated pseudo-measurement approach is an efficient algorithm for the distributed tracking problem. In this paper, we use an existing multiple-lag out-of-sequence measurement (OOSM) algorithm and the decorrelated pseudo-measurement approach for track-to-track fusion of out-of-sequence track (OOST) data. We present numerical results using simulated data for a scenario where a global tracker processes track data from two local trackers. Each local tracker processes two-dimensional position and velocity measurements from a single sensor. We use Monte Carlo simulations to evaluate the performance of the algorithm.

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