Joint Angle and Delay Estimation (JADE) Algorithm MATLAB Implementation

This article provides a comprehensive introduction to the MATLAB implementation of the Joint Angle and Delay Estimation (JADE) algorithm. We begin by explaining the theoretical background and fundamental principles of the JADE algorithm to establish a solid foundation for understanding the program implementation. The implementation includes key components such as signal covariance matrix computation, eigenvalue decomposition for signal subspace extraction, and parameter estimation through spatial spectrum analysis. We then systematically walk through each program module and function, covering input/output specifications, data preprocessing techniques, signal decomposition methods, and signal reconstruction procedures. The implementation features MATLAB's signal processing toolbox functions for array signal processing and incorporates optimization techniques for computational efficiency. Detailed code annotations and practical examples are provided to demonstrate proper usage of the functions, including parameter configuration for different antenna array geometries and signal scenarios. The code includes error handling for invalid inputs and validation checks for estimation accuracy. Through studying this material, readers will gain deeper insights into JADE algorithm applications and implementation techniques, providing valuable support for subsequent research and development work in array signal processing and parameter estimation.