[Communication simulation] DOA estimation of broadband signal (chirp signal) based on matlab music algorithm

Broadband signal flow of MUSIC algorithm based on MATLAB

For DOA estimation of wideband signal (chirp signal) based on MATLAB's MUSIC algorithm, the following steps can be followed:

1. Construct broadband signals: Construct multiple sine waves with different frequencies to form broadband signals.

2. Simulate an array: Simulate an array with N sensors and sample the broadband signal received by each sensor.

3. Parameter setting: set the parameters related to DOA estimation according to the actual situation, such as signal-to-noise ratio, angle search range, angle resolution, etc.

4. Calculation of covariance matrix: Covariance operation is performed on the sampled broadband signal in time and space to obtain covariance matrix R.

5. Calculation of eigenvalue decomposition: By performing eigenvalue decomposition on the covariance matrix, its eigenvalues ​​and eigenvectors are obtained.

6. Calculating the noise subspace: the matrix composed of eigenvectors with smaller eigenvalues ​​is used as the noise subspace to estimate the number of signal sources.

7. Calculating the spatial spectrum: The matrix composed of eigenvectors with large eigenvalues ​​is used as the signal subspace, and the DOA estimation result is obtained by performing spatial spectrum estimation on the signal subspace, which is the core part of the MUSIC algorithm.

It should be noted that the above steps may vary due to different actual scenarios and parameter settings.

Code

The following is the code implementation of DOA estimation for wideband signal (chirp signal) based on MATLAB's MUSIC algorithm, for reference:

%% 基于 MATLAB 的 MUSIC 算法宽带信号（线性调频信号&#