Joint target positioning and sensor bias estimation with range only measurements

A target can be positioned by wireless communication sensors. When the range based sensors have biased measurements, an Expectation Maximization (EM) algorithm is proposed to jointly estimate the target state and sensors´ biases, including the batch EM and sliding window EM algorithms. To implement the algorithms, the Iterated Extended Kalman Smoother (IEKS) is also embedded in the EM algorithm. The simulation results show that the batch algorithm has the best estimation performance. The sliding window EM algorithm has better estimation performance than the augmented UKF (AUKF) algorithm. Since batch EM algorithm is not suitable for real time estimation scenario, the sliding window EM algorithm is recommended for real time target positioning.