An SOCP Estimator for Hybrid RSS and AOA Target Localization in Sensor Networks

Abstract

This work addresses the problem of target localization in three-dimensional wireless sensor networks (WSNs). The proposed algorithm is based on a hybrid system that employs angle of arrival (AOA) and received signal strength (RSS) measurements, where the target’s transmit power is considered as an unknown parameter. Although both cases of a known and unknown target’s transmit power have been addressed in the literature, most of the existing approaches for unknown transmit power are either carried out recursively, or require a high computational cost. This results in an increased execution time of these algorithms, which we avoid in this work by proposing a single-iteration solution with moderate computational complexity. By exploiting the measurement models, a non-convex least squares (LS) estimator is derived first. Then, to tackle its nonconvexity, we resort to second-order cone programming (SOCP) relaxation techniques to transform the non-convex estimator into a convex one. Additionally, to make the estimator tighter, we exploit the angle between two vectors by using the definition of their inner product, which arises naturally from the derivation steps that are taken. The proposed method not only matches the performance of a computationally more complex state-of-the-art method, but it outperforms it for small N. This result is of a significant value in practice, since one desires to localize the target using the least number of anchor nodes as possible due to network costs.

Majorization-Minimization based Hybrid Localization Method for High Precision Localization in Wireless Sensor Networks

“…The authors of [29] dealt with the differential RSS and AOA measurement model and proposed a selective hybrid measurement weighted instrumentation variable (SHM-WIV) method. Similar to the case of known transmitted power, the models based on unknown transmission power were also generally solved using the WLS approach [30]- [36]; in which the non-convex WLS problem was usually relaxed to a convex problem and solved as either SDP [31], [32] or as SOCP [33]- [35].…”

Closed-Form Pseudolinear Estimators for DRSS-AOA Localization

“…Hybrid DRSS-AOA localization has not attracted much research despite the great potential it offers as a feasible and low-cost localization method compared with RSS-AOA and TDOA-AOA methods. The work in [41] proposes a hybrid RSS-AOA localization algorithm that treats the transmit power as unknown parameter, based on second-order cone programming relaxation techniques. In this paper, we present new hybrid localization algorithms using DRSS and AOA measurements based on the PLE and its instrumental variable variants.…”