Development of a 2-dimensional angulation algorithm target locating error estimation technique

A multiangulation (MANG) system determines an emitting target location using the angle of arrival (AOA) measurement estimated from its emission with an angulation algorithm. Prior to deployment of the system, it is important to know if the horizontal coordinate (HC) root mean square error (RMSE)s obtained by the system at certain target locations given an AOA error are within approved standards set by the international regulatory bodies. For this reason, a MANG system target locating error estimation technique based on Euclidean geometrical analysis and linear regression is proposed in this paper. This is to assist in the systematic determination and prediction of the HC RMSE obtained by the angulation algorithm of the MANG system. The proposed technique is validated by comparison with the Monte Carlo (MC) simulation at some randomly selected target locations using a square receiving station (RS) configuration. Result comparison shows that the proposed technique predicts the target HC RMSE obtained by the angulation algorithm within a system coverage of 10 km by 10 km with a prediction accuracy of about ±5 m.Keywords: Multiangulation system; Angle of arrival: Angulation Algorithm; Error prediction; Linear regressio

Group sparsity based target localization for distributed sensor array networks

The target localization problem for distributed sensor array networks where a sub-array is placed at each receiver is studied, and under the compressive sensing (CS) framework, a group sparsity based two-dimensional localization method is proposed. Instead of fusing the separately estimated angles of arrival (AOAs), it processes the information collected by all the receivers simultaneously to form the final target locations. Simulation results show that the proposed localization method provides a significant performance improvement compared with the commonly used maximum likelihood estimator (MLE)

Multiangulation position estimation performance analysis using a Bartlett’s Beamforming Method

In this work, a complete multiangulation system was developed and its performance in term of position estimation (PE) was determined. The developed system uses Bartlett’s beam forming method to estimate AOA of the signal impinging on the 16-element sensor array in a uniform linear array (ULA) geometry at each ground receiving station (GRS). The AOA measurements are then used as input to a linear angulation algorithm for PE. The PE accuracy of the developed system was determined using Monte Carlo simulation and compared with the directional rotating antenna multiangulation system using a square GRS configuration. Simulation results shows that the developed multiangulation PE error is 50% lower than that of the directional rotating antenna system. Furthermore, the PE error of the developed system is higher for emitting sources within the system coverage with position bearings within 610 to 1200 and 2400 to 3000 than other emitting source locations.Keywords: multiangulation system, position estimation, beam forming, Monte Carlo Simulation, position bearin

Exploiting Orientation Information to Improve Range-Based Localization Accuracy

Funding Information: This work supported in part by the Fundação para a Ciência e a Tecnologia under Project IF/00325/2015, Project foRESTER PCIF/SSI/0102/2017, and Project UIDB/04111/2020, and in part by the Universidade Lusófona/ILIND internal project TESLA.This work addresses target localization problem in precarious surroundings where possibly no links are line of sight. It exploits the known architecture of available reference points to act as an irregular antenna array in order to estimate the azimuth angle between a reference point and a target, based on distance estimates withdrawn from integrated received signal strength (RSS) and time of arrival (TOA) observations. These fictitious azimuth angle observations are then used to linearize the measurement models, which triggers effortless derivation of a new estimator in a closed-form. It is shown here that, by using fixed network geometry in which target orientation with respect to a line formed by a pair of anchors can be correctly estimated, the localization performance can be significantly enhanced. The new approach is validated through computer simulations, which corroborate our intuition of profiting from inherent information within a network.publishersversionpublishe

Positioning of Radio Emission Sources with Unmanned Aerial Vehicles using TDOA-AOA Measurement Processing

Actual trends in current passive geolocation system development includes cooperation of flying segment based on receiver stations aboard Unmanned Aerial Vehicles (UAVs) with terrestrial segment including stationary ground receiver stations. Existing accuracy results achieves the order of tens and hundreds of meters in optimistic Line of Sight (LOS) conditions. However, the problem of radio emission sources positioning with UAVs is especially relevant for search and rescue operations in heterogeneous terrain, when separate primary measurements obtained, for example, after reflections, could lead to a significant error. One possible way to improve the accuracy of positioning in such conditions is to use aerial passive geolocation based on UAVs with joint processing of Time Difference of Arrival (TDOA) and Angle of Arrival (AOA) primary measurements. The contribution of the current investigation is the development of mathematical model for positioning of radio emission sources with UAVs using TDOA-AOA measurement processing.This work was supported by the Ministry of Science and Education of the Russian Federation with Grant of the President of the Russian Federation for the state support of young Russian scientists № MK-3468.2018.9

Near-Field Integrated Sensing, Positioning, and Communication: A Downlink and Uplink Framework

A near-field integrated sensing, positioning, and communication (ISPAC) framework is proposed, where a base station (BS) simultaneously serves multiple communication users and carries out target sensing and positioning. A novel double-array structure is proposed to enable the near-field ISPAC at the BS. Specifically, a small-scale assisting transceiver (AT) is attached to the large-scale main transceiver (MT) to empower the communication system with the ability of sensing and positioning. Based on the proposed framework, the joint angle and distance Cram\'er-Rao bound (CRB) is first derived. Then, the CRB is minimized subject to the minimum communication rate requirement in both downlink and uplink ISPAC scenarios: 1) For downlink ISPAC, a downlink target positioning algorithm is proposed and a penalty dual decomposition (PDD)-based double-loop algorithm is developed to tackle the non-convex optimization problem. 2) For uplink ISPAC, an uplink target positioning algorithm is proposed and an efficient alternating optimization algorithm is conceived to solve the non-convex CRB minimization problem with coupled user communication and target probing design. Both proposed optimization algorithms can converge to a stationary point of the CRB minimization problem. Numerical results show that: 1) The proposed ISPAC system can locate the target in both angle and distance domains merely relying on single BS and limited bandwidths; and 2) the positioning performance achieved by the hybrid-analog-and-digital ISPAC approaches that achieved by fully digital ISPAC when the communication rate requirement is not stringent.Comment: 13 pages, 6 figure

Efficient underwater acoustical localization method based on time difference and bearing measurements

This article addresses the underwater acoustical localization problem by using the time-difference-of-arrival (TDOA) and bearing-angle-of-arrival (BAOA) measurements. For the underwater acoustic equipment, such as the ultrashort baseline system (USBL), whose bearing measurements are different from the traditional angle-of-arrival (AOA) model, a closed-form solution for the hybrid TDOA/BAOA-based source localization problem is developed. However, the solution suffers from the measurement noise and cannot achieve the Cramer–Rao lower bound (CRLB) performance in the case of large measurement noise. Thus, an iterative constrained weighted least-squares method is presented to further minimize the error in the case of large noise. The CRLB for hybrid TDOA/BAOA source localization is analyzed, and the solution is proved to achieve the CRLB performance. Numerical simulations and field tests demonstrate that the proposed method outperforms the traditional methods in terms of estimation bias and accuracy. It can achieve the CRLB performance better