Bearing angle measurements in RF systems having normally distributed arrival angle with unknown variance

In order to improve the tracking accuracy of the synchronous radar network under blanket jamming with less computation, a new target tracking algorithm based on the optimal linearization is proposed. Firstly, the optimal linearization algorithm for the measurement equation is analyzed. Then the optimal estimation of the position is derived in 2D space according to the bearing angle measurements, and then the estimation is expanded to 3D space in accordance with the pitch angle measurements. Finally, the tracking algorithm for the moving target is presented and simulation testing is conducted. The simulation results show the tracking algorithm without iteration proposed by this paper can make it possible for the radar network under blanket jamming to track the target precisely.

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Fusion of Angle Measurements from Hull Mounted and Towed Array Sensors

Information ◽

10.3390/info11090432 ◽

2020 ◽

Vol 11 (9) ◽

pp. 432

Author(s):

Kausar Jahan ◽

Koteswara Rao Sanagapallea

Keyword(s):

Sensor Array ◽

Sensor Arrays ◽

Convergence Time ◽

Fusion Algorithm ◽

Angle Measurements ◽

Solution Convergence ◽

Bearing Angle ◽

Single Sensor ◽

Towed Array ◽

Using Data

Two sensor arrays, hull-mounted array, and towed array sensors are considered for bearings-only tracking. An algorithm is designed to combine the information obtained as bearing (angle) measurements from both sensor arrays to give a better solution. Using data from two different sensor arrays reduces the problem of observability and the observer need not follow the S-maneuver to attain observability of the process. The performance of the fusion algorithm is comparable to that of theoretical Cramer–Rao lower bound and with that of the algorithm when bearing measurements from a single sensor array are considered. Different filters are used for analyzing both algorithms. Monte Carlo runs need to be done to evaluate the performance of algorithms more accurately. Also, the performance of the fusion algorithm is evaluated in terms of solution convergence time.

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Cooperative vehicle localisation method based on the fusion of GPS, inter-vehicle distance, and bearing angle measurements

IET Intelligent Transport Systems ◽

10.1049/iet-its.2018.5091 ◽

2019 ◽

Vol 13 (4) ◽

pp. 644-653

Author(s):

Xiaolin Song ◽

Yifei Ling ◽

Haotian Cao ◽

Zhi Huang

Keyword(s):

Angle Measurements ◽

Bearing Angle

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Dynamic Prediction-Based Optical Localization of a Robot During Continuous Movement

Volume 2: Intelligent Transportation/Vehicles; Manufacturing; Mechatronics; Engine/After-Treatment Systems; Soft Actuators/Manipulators; Modeling/Validation; Motion/Vibration Control Applications; Multi-Agent/Networked Systems; Path Planning/Motion Control; Renewable/Smart Energy Systems; Security/Privacy of Cyber-Physical Systems; Sensors/Actuators; Tracking Control Systems; Unmanned Ground/Aerial Vehicles; Vehicle Dynamics, Estimation, Control; Vibration/Control Systems; Vibrations ◽

10.1115/dscc2020-3288 ◽

2020 ◽

Author(s):

Jason N. Greenberg ◽

Xiaobo Tan

Keyword(s):

Mobile Robots ◽

Traditional Approach ◽

Dynamic Prediction ◽

Angle Measurements ◽

Continuous Movement ◽

Localization Scheme ◽

Stop And Go ◽

Bearing Angle ◽

Velocity Prediction ◽

Location Measurement

Abstract Localization of mobile robots is essential for navigation and data collection. This work presents an optical localization scheme for mobile robots during the robot’s continuous movement, despite that only one bearing angle can be captured at a time. In particular, this paper significantly improves upon our previous works where the robot has to pause its movement in order to acquire the two bearing angle measurements needed for position determination. The latter restriction forces the robot to work in a stop-and-go mode, which constrains the robot’s mobilitty. The proposed scheme exploits the velocity prediction from Kalman filtering, to properly correlate two consecutive measurements of bearing angles with respect to the base nodes (beacons) to produce location measurement. The proposed solution is evaluated in simulation and its advantage is demonstrated through the comparison with the traditional approach where the two consecutive angle measurements are directly used to compute the location.

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