详情

原文传递 Non-Linear Optimization Applied to Angle-of-Arrival Satellite Based Geo-Localization for Biased and Time Drifting Sensors.

题名：	Non-Linear Optimization Applied to Angle-of-Arrival Satellite Based Geo-Localization for Biased and Time Drifting Sensors.
作者：	Levy, D. E.
关键词：	Artificial satellites, Statistical analysis, Monte carlo method, Elliptical orbits, Computer vision, Angle of arrival, Random walk, Measurement, Estimators, Coordinate systems, Algorithms, Accuracy, Optimization, Tracking, Bias, Nonlinear systems, Detectors, Geolocation, Non-linear optimization, Passive tracking
摘要：	Multiple sensors are used in a variety of geolocation systems. When an object does not emit a classical RF signal, AOA measurements become more feasible than TDOA or RSS methods. A NLO method for calculating the most likely estimate from AOA measurements has been created in previous work. This thesis modifies that algorithm to automatically correct AOA measurement errors by estimating the inherent bias and time-drift in the IMU of the AOA sensing platform. Two methods are created to correct the sensor bias. One method corrects the sensor bias in post processing while treating the previous NLO method as a module. The other method directly corrects the sensor bias within the NLO algorithm by incorporating the bias parameters as a state vector in the estimation process. These two methods are analyzed using various Monte-Carlo simulations to check the general performance of the two modifications in comparison to the original NLO algorithm.
报告类型：	科技报告