Wireless sensor localization using enhanced DV-AoA algorithm

Abstract

Abstract:In this paper, we deal with the improvement of the positioning accuracy of distance vector (DV)-based positioning algorithms, which use angular information DV-angle of arrival (AoA). This algorithm belongs to an adhoc positioning system. We focus on the improvement of the algorithm and its enhanced version is presented. The angular information of particular nodes is obtained and processed by the original algorithm; however, the final position estimation is determined by the proposed novel algorithm using only a subset of all intersections. We assign weights to the individual intersections according to their positions and the positions of the RNs. For the final position estimation, only intersections with the highest weights are used. The performance of the proposed enhanced algorithm is verified by simulations and it is compared with the original DV-AoA algorithm.

Sparse Localization with a Mobile Beacon Based on LU Decomposition in Wireless Sensor Networks

“…Niculescu and Nath [4], Nasipuri and Li [5] proposed some other schemes to estimate relative angles between one-hop neighboring nodes for angulations. Brida et al [6] propose an enhanced DV-AOA algorithm. The angular information of nodes is ensured and processed by the original algorithm; however, the final location estimation is determined by the proposed novel algorithm using only a subset of all intersections.…”

“…where Then, U can be ensured by the following Schmidt normalization process (6) where U 1 , U 2 , …, U N are column vectors of the unitary matrix U . From the above analysis and [23], it can be seen that the measurement matrix Q is an incoherent measurement (one of the most common measurement matrices in CS).…”

“…The existing localization techniques can be classified into range-based schemes and range-free schemes. The range-based schemes need to measure the distance between two neighbor nodes [1][2][3][4][5][6], in which the distance is calculated based on received signal strength (RSS), time of arrival (TOA), time difference of arrival (TDOA), or angle of arrival (AOA). The range-based schemes have two obvious weaknesses: the nodes require additional measuring equipment and the localization accuracy is vulnerable to the environmental interference.…”

Indoor localization of wireless emitter using direct position determination and particle swarm optimization

“…Noting that GPS systems are inadequate due to the multipath or signal blocked indoors, widespread localization techniques have been used for positioning with wireless access points [1]. The most common techniques are based on measuring the received signal strength indication (RSSI) and methods of fingerprint, time difference delay of arrival signal (TDOA), frequency difference of arrival (FDOA), and angle of arrival (AOA) of signals [2,3]. These methods use a two-stage process to estimate the position but are not necessarily optimal, because in the first stage of these methods the location-dependent parameters are obtained by ignoring the fact that all measurements should be consistent with a single emitter location [4].…”