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.
Highlights
Indoor positioning systems for wireless sensor network (WSN) have become very popular and been used successfully in a variety of scenarios, such as location detection and tracking of products stored in a warehouse, and people within buildings such as hospitals and nursing homes
The following propositions show that the filtered estimates bxm(i) and bxa(i) for moving target’s position, velocity, and acceleration have a deadbeat property when there are no noises in the discrete-time, state-space model (1) with measurement delay
The alternative indoor positioning mechanism has been proposed for WSNs
Summary
Indoor positioning systems for wireless sensor network (WSN) have become very popular and been used successfully in a variety of scenarios, such as location detection and tracking of products stored in a warehouse, and people within buildings such as hospitals and nursing homes. Existing indoor positioning mechanisms adopt these estimation filters in Basin and Zuniga,[15] Zhang et al.,[16] and Lu et al.[17,18] to deal with a measurement delay, they can still show poor performance and even divergence phenomenon for temporary modeling uncertainties and numerical errors. In this article, an alternative indoor positioning mechanism is proposed considering FMS filter as well as measurement delays. The proposed FMS filtering based mechanism gives the filtered estimates for position and velocity of moving target in real time, while removing undesired noisy effects and preserving desired moving locations. The proposed FMS filtering–based indoor positioning in WSN estimates moving target’s random position in real time, removing undesired noisy effects, while preserving desired position. The FMS filter uses only the most recent finite measurements Z(i) on the window 1⁄2i À M, i as follows
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