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Performance Analysis of the Direct Position Determination Method in the Presence of Array Model Errors.
Ding Wang1,2, Hongyi Yu3,4, Zhidong Wu5,6
1National Digital Switching System Engineering & Technological Research Center, Zhengzhou 450002, China. wang_ding814@aliyun.com.
Sensors (Basel, Switzerland)
|July 4, 2017
Summary
This study analyzes the direct position determination (DPD) technique for source localization. It theoretically evaluates DPD performance under array model errors, providing insights into localization accuracy and error influences.
Area of Science:
- Signal Processing
- Estimation Theory
- Array Signal Processing
Background:
- Direct Position Determination (DPD) offers higher accuracy than conventional two-step localization.
- Understanding DPD performance under real-world conditions, like array model errors, is crucial.
Purpose of the Study:
- To theoretically analyze the performance of a Direct Position Determination estimator proposed by Weiss.
- To investigate the impact of array model errors on the accuracy of DPD.
Main Methods:
- Utilized matrix eigen-perturbation theory to analyze error propagation.
- Derived first-order asymptotic expressions for positioning errors.
- Developed analytical expressions for mean square error and probabilities of successful localization.
- Derived Cramér-Rao bounds for position estimation with and without array model errors.
Main Results:
- Provided an analytical expression for the mean square error of direct localization.
- Derived explicit formulas for successful localization probabilities.
- Quantified the impact of array model errors on localization accuracy through Cramér-Rao bounds.
Conclusions:
- The theoretical framework developed offers insights into DPD performance under array model errors.
- The derived Cramér-Rao bounds are valuable for assessing localization accuracy limitations.
- Simulation results validate the theoretical findings regarding DPD performance and error analysis.
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