RSS-Based Localization of Multiple Directional Sources With Unknown Transmit Powers and Orientations

Abstract

Received-signal-strength (RSS)-based localization has received widespread attention recently. Due to the simple acquisition of the RSS measurements, the adequate inexpensive sensors in sensor networks are capable of providing the information needed for the positioning of multiple target sources. However, few studies have focused on the RSS-based localization of multiple directional sources that are common in reality. Based on the deduced parametric Optimal Maximum Likelihood (OML) solution, this paper proposes three new grid search-based algorithms, namely Alternating Projection (i.e., OMLAP) algorithm, Expectation-Maximization like (i.e., OMLEM) algorithm, and Particle Swarm Optimization (i.e., OMLPSO) algorithm. They can be utilized for estimating the transmit powers, locations, and orientations of multiple directional sources. Combining the interpolation process and proposed power threshold setting method, the search space is obviously reduced. Moreover, the corresponding Cramer-Rao lower bounds (CRLB) are also derived to characterize the estimation accuracy of the algorithms. Both the scenarios with different Signal-to-Noise Ratios (SNRs) and the scenarios with different sensor quantities are considered in the simulation, and the results demonstrate the effectiveness of the proposed algorithms and indicate that they are suitable for the parameter estimation of multiple directional sources.

Stationary target localization and circumnavigation by a non‐holonomic differentially driven mobile robot: Algorithms and experiments

“…This effectively reduces the measuring burden and relieves the payload of the mobile robot. For this purpose, many efforts have been made for the solution to the localization and circumnavigation problem by using distance‐only measurements, 14‐16 bearing‐only measurements, 17‐19 and received signal strength (RSS) measurements 20‐23 . In particular, by using the continuous distance measurement with respect to the target, the authors of References 15 and 16 proposed feasible control algorithms such that the concerned mobile agent was capable of localizing and circumnavigating the target as prescribed.…”

Geolocation of Multiple Noncooperative Emitters Using Received Signal Strength: Sparsity, Resolution, and Detectability

“…But many focus on situations in which the emitters are cooperative [18], or only one emitter is present, or emitters can be distinguished in some manner in the data ( [19], [22], [24]). The interesting recent paper [25] considers the problem of multiple directional RF emitters, although the authors assume the number of emitters is known a priori, and they use an additive noise model rather than the more conventional lognormal noise model. They also provide a Cramer-Rao based estimate on the accuracy that their methods might attain.…”

“…This improves the channel model and accuracy of emitter location estimates. Some methods focus on prediction of lower bounds for the variance of location estimates from RSS data [29]- [31], and the above-mentioned [25], [26].…”

Lifetime and Energy Efficiency Improvement Techniques for Hierarchical Networks

“…The Received-signal-strength (RSS) is computed for the various sensors in order inject the detection points in the network graph. The estimation of power, determination of location along with direction of sources is done by various algorithms [2].…”