A Closed-Form Localization Algorithm Using Angle-of-Arrival and Difference Time of Scan Time Measurements in Scan-Based Radar

2019 ◽  
Vol 55 (1) ◽  
pp. 511-515 ◽  
Author(s):  
WanChun Li ◽  
YingXiang Li ◽  
Ping Wei ◽  
Heng-Ming Tai
Keyword(s):  
Closed Form ◽  
Localization Algorithm ◽  
Angle Of Arrival ◽  
Scan Time ◽  
Difference Time

scholarly journals Performance Analysis of AOA-Based Localization Using the LS Approach: Explicit Expression of Mean-Squared Error

2020 ◽  
Vol 2020 ◽  
pp. 1-22
Author(s):  
Byung-Kwon Son ◽  
Do-Jin An ◽  
Joon-Ho Lee
Keyword(s):  
Explicit Expression ◽  
Mean Squared Error ◽  
Weighted Least Squares ◽  
Localization Algorithm ◽  
Angle Of Arrival ◽  
Squared Error ◽  
Distance Weighted ◽  
The Mean ◽  
Passive Localization ◽  
Location Estimate

In this paper, a passive localization of the emitter using noisy angle-of-arrival (AOA) measurements, called Brown DWLS (Distance Weighted Least Squares) algorithm, is considered. The accuracy of AOA-based localization is quantified by the mean-squared error. Various estimates of the AOA-localization algorithm have been derived (Doğançay and Hmam, 2008). Explicit expression of the location estimate of the previous study is used to get an analytic expression of the mean-squared error (MSE) of one of the various estimates. To validate the derived expression, we compare the MSE from the Monte Carlo simulation with the analytically derived MSE.

scholarly journals Probability Weighting Localization Algorithm Based on NLOS Identification in Wireless Network

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Shixun Wu ◽  
Shengjun Zhang ◽  
Kai Xu ◽  
Darong Huang
Keyword(s):  
Base Station ◽  
Line Of Sight ◽  
Time Of Arrival ◽  
Probability Weighting ◽  
Localization Algorithm ◽  
Angle Of Arrival ◽  
Chi Square ◽  
Home Base ◽  
Angle Measurements ◽  
Non Line Of Sight

In this paper, a localization scenario that the home base station (BS) measures time of arrival (TOA) and angle of arrival (AOA) while the neighboring BSs only measure TOA is investigated. In order to reduce the effect of non-line of sight (NLOS) propagation, the probability weighting localization algorithm based on NLOS identification is proposed. The proposed algorithm divides these range and angle measurements into different combinations. For each combination, a statistic whose distribution is chi-square in LOS propagation is constructed, and the corresponding theoretic threshold is derived to identify each combination whether it is LOS or NLOS propagation. Further, if those combinations are decided as LOS propagation, the corresponding probabilities are derived to weigh the accepted combinations. Simulation results demonstrate that our proposed algorithm can provide better performance than conventional algorithms in different NLOS environments. In addition, computational complexity of our proposed algorithm is analyzed and compared.

An Improved Mono-Station UWB TOA/AOA Positioning Method

2012 ◽  
Vol 229-231 ◽  
pp. 1373-1376
Author(s):  
Xiao Dong Tu ◽  
Hao Zhang ◽  
Xue Rong Cui ◽  
Xing Liu
Keyword(s):  
Antenna Array ◽  
Pulse Amplitude ◽  
Base Station ◽  
Ultra Wideband ◽  
Localization Algorithm ◽  
Angle Of Arrival ◽  
Maximum Slope ◽  
Reference Base ◽  
Positioning Method ◽  
System Requirements

The paper proposes a mono-station TOA/AOA positioning method based on ultra-wideband (UWB) antenna array. The article calculates accurately the signal's angle of arrival (AOA) by measurement of the UWB-pulse amplitude of the reference base-station antenna array received, combined with the antenna beam pattern. With the estimation of the information of arrival time using the skewness and the maximum slope, the location of the label can be found. The ranging error of the localization algorithm can achieve centimeter-level and angle of arrival is less than or equal to 1.0.In the paper, the accuracy of positioning method is not affected, eliminating the high-precision synchronization requirements of the traditional reference base-station and significantly reducing the system requirements of clock accuracy and system complexity.

A Localization Algorithm of Multi-Hop Three Dimensional AOA with Space-Based Angle Transmission and its Application

2013 ◽  
Vol 756-759 ◽  
pp. 3562-3567
Author(s):  
Qing Zhang Chen ◽  
Yun Feng Ni ◽  
Xing Hua Li ◽  
Rong Jie Wu ◽  
Yan Jing Lei ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Angle Of Arrival ◽  
Terrain Modeling ◽  
Terrain Model ◽  
Anchor Nodes ◽  
Slow Progress ◽  
Positioning Algorithm

Wireless sensor node's localization is a funda-mental technology in Wireless Sensor Networks. There are only quite a few study on three-dimensional (3D) localization which is suffered in slow progress, actually, is one of the main difficulties in WSN localization. Based on the study of the existing two-dimensional positioning algorithm and the application of terrain modeling, localization algorithm for sensor nodes in (3D) condition has been focus on as well as the application of terrain model. Using the idea proposed by representative algorithm--APS multi-hop AOA (Angle of Arrival), this paper proposed a new algorithm named Multi-hop Three Dimensional AOA With Space-based Angle Trans-mission (MSAT3D AOA). Using this technology, target nodes can use information of anchor nodes which are more than one hop away form. This paper also combined MSAT3D AOA algorithm with Delaunay triangulation algorithm for terrain modeling.

scholarly journals A Single-Way Ranging Localization of AUVs Based on PSO of Outliers Elimination

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Xinnan Fan ◽  
Zhongjian Wu ◽  
Jianjun Ni ◽  
Chengming Luo
Keyword(s):  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Time Of Arrival ◽  
Localization Algorithm ◽  
Angle Of Arrival ◽  
Simulation Experiments ◽  
Range Measurements ◽  
Acoustic Localization ◽  
Long Baseline ◽  
Key Factor

Localization of autonomous underwater vehicles (AUVs) is a very important and challenging task for the AUVs applications. In long baseline underwater acoustic localization networks, the accuracy of single-way range measurements is the key factor for the precision of localization of AUVs, whether it is based on the way of time of arrival (TOA), time difference of arrival (TDOA), or angle of arrival (AOA). The single-way range measurements do not depend on water quality and can be taken from long distances; however, there are some limitations which exist in these measurements, such as the disturbance of the unknown current velocity and the outliers caused by sensors and errors of algorithm. To deal with these problems, an AUV self-localization algorithm based on particle swarm optimization (PSO) of outliers elimination is proposed, which improves the performance of angle of arrival (AOA) localization algorithm by taking account of effects of the current on the positioning accuracy and eliminating possible outliers during the localization process. Some simulation experiments are carried out to illustrate the performance of the proposed method compared with another localization algorithm.

scholarly journals Multi-Target Localization Based on Unidentified Multiple RSS/AOA Measurements in Wireless Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4455
Author(s):  
Seyoung Kang ◽  
Taehyun Kim ◽  
Wonzoo Chung
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Complexity Analysis ◽  
Target Localization ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Angle Of Arrival ◽  
Computationally Efficient ◽  
Localization Algorithms ◽  
Single Target

All existing hybrid target localization algorithms using received signal strength (RSS) and angle of arrival (AOA) measurements in wireless sensor networks, to the best of our knowledge, assume a single target such that even in the presence of multiple targets, the target localization problem is translated to multiple single-target localization problems by assuming that multiple measurements in a node are identified with their originated targets. Herein, we first consider the problem of multi-target localization when each anchor node contains multiple RSS and AOA measurement sets of unidentified origin. We propose a computationally efficient method to cluster RSS/AOA measurement sets that originate from the same target and apply the existing single-target linear hybrid localization algorithm to estimate multiple target positions. The complexity analysis of the proposed algorithm is presented, and its performance under various noise environments is analyzed via simulations.

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