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A contribution to performance prediction for probabilistic data association tracking filters

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2 Author(s)
Kershaw, D.J. ; Aeronaut. & Maritime Res. Lab., DSTO, Melbourne, Vic., Australia ; Evans, R.J.

The probabilistic data association (PDA) algorithm for tracking in clutter contains a stochastic (data-dependent) Riccati equation for updating the estimation error covariance matrix. This note details a simple analytic approximation to the stochastic Riccati equation that allows precomputation of the estimation error covariance matrices. The potential of the approximation for performance analysis of PDA-based tracking algorithm is demonstrated using a simple example.

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Aerospace and Electronic Systems, IEEE Transactions on  (Volume:32 ,  Issue: 3 )