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Joint Entropy Error Bound of Two-Dimensional Direction-of-Arrival Estimation for L-Shaped Array
Xiaolong Kong1, Daxuan Zhao1, Nan Wang1
1The Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
This study introduces a new Azimuth and Elevation Direction-of-Arrival Entropy Error Bound (AEEEB) for L-shaped arrays. The AEEEB offers a tighter performance bound than the Cramér-Rao bound (CRB) in low and medium signal-to-noise ratio regions.
Area of Science:
- Signal Processing
- Array Signal Processing
- Estimation Theory
Background:
- Direction-of-Arrival (DOA) estimation accuracy is crucial in various applications.
- Existing performance lower bounds, like the Cramér-Rao bound (CRB), lack tightness in low signal-to-noise ratio (SNR) regions for joint DOA estimation.
- Joint estimation of azimuth and elevation DOAs requires robust performance bounds.
Purpose of the Study:
- To propose a novel and tight performance lower bound for the joint estimation of azimuth and elevation DOAs.
- To address the limitations of the CRB in low- and medium-SNR conditions.
- To evaluate the proposed bound using an L-shaped array configuration.
Main Methods:
- Derivation of the joint conditional probability density function (PDF) relating the received signal to DOA parameters.
- Application of Bayesian theorem to derive the joint a posteriori PDF.
- Development of the Azimuth and Elevation DOA Entropy Error Bound (AEEEB) based on joint a posteriori entropy.
- Comparison with the Cramér-Rao bound (CRB) and Mean Square Error (MSE) through simulations.
Main Results:
- The proposed Azimuth and Elevation DOA Entropy Error Bound (AEEEB) was successfully derived for an L-shaped array.
- Simulations demonstrated that the AEEEB provides a tighter performance bound compared to the traditional CRB.
- The AEEEB shows improved accuracy in low- and medium-SNR regions for joint DOA estimation.
Conclusions:
- The AEEEB is a more accurate and tighter performance bound for joint azimuth and elevation DOA estimation than the CRB, especially in challenging SNR conditions.
- This novel bound enhances the evaluation of DOA estimation algorithms in practical scenarios.
- The findings contribute to the advancement of array signal processing techniques.
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