We propose a new position location algorithm based on the bootstrap filtering using the time difference of arrival measurements. The proposed algorithm imposes nonlinear kinematic constraints on the state estimates without destabilizing the algorithm. Such constraints can be most naturally incorporated in the Bayesian bootstrap filtering framework. The proposed algorithm is verified through simulation, and the result demonstrates that our algorithm is more robust than the extended Kalman filter and the bootstrap filter without constraints.
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