A finite memory structure filtering for indoor positioning in wireless sensor networks with measurement delay

Abstract

In this article, an alternative indoor positioning mechanism is proposed considering finite memory structure filter as well as measurement delay. First, a finite memory structure filter with a measurement delay is designed for the indoor positioning mechanism under a weighted least-squares criterion, which utilizes only finite measurements on the most recent window. The proposed finite memory structure filtering–based mechanism gives the filtered estimates for position, velocity, and acceleration of moving target in real time, while removing undesired noisy effects and preserving desired moving positions. Second, the proposed mechanism is shown to have good inherent properties such as unbiasedness, efficiency, time-invariance, deadbeat, and robustness due to the finite memory structure. Third, through discussions about the choice of window length, it is shown that this can be considered as a useful design parameter to make the performance of the proposed mechanism as good as possible. Finally, computer simulations show that the performance of the proposed finite memory structure filtering–based mechanism can outperform the existing infinite memory structure filtering–based mechanism for the abruptly varying acceleration of moving target.