Adaptive Null Widening Beamforming Algorithm in Spatially Correlated Color Noise

Area of Science:

• Signal Processing
• Adaptive Beamforming
• Electromagnetic Interference

Background:

• High-speed platforms face degraded anti-jamming performance due to rapidly changing jamming signal incidence angles.
• Spatially correlated color noise further exacerbates waveform distortion in adaptive beamformers.
• Existing robust adaptive beamforming algorithms struggle to maintain performance under these conditions.

Purpose of the Study:

• To propose a projection-constrained null broadening beamforming algorithm for improved anti-jamming capabilities.
• To address the challenges posed by spatially correlated color noise and rapidly changing incidence angles.
• To enhance the signal-to-interference-plus-noise ratio (SINR) of adaptive beamformers.

Main Methods:

• Utilizes Toeplitz matrix structure for beamforming algorithm design.
• Extracts subspace from the covariance matrix of steering vectors within a defined angle interval.
• Constructs constraint and projection transformation matrices.
• Forms a Toeplitz structured received signal covariance matrix.
• Applies projection transformation and constrains array element weights.

Main Results:

• The proposed algorithm achieves the theoretical optimal solution for adaptive wide null beamforming in spatially correlated color noise.
• Simulation results demonstrate significant improvement in adaptive anti-jamming beam distortion compared to existing algorithms.
• The algorithm successfully achieves null broadening in the jamming direction.
• The output SINR of the adaptive beamformer is effectively improved.

Conclusions:

• The novel projection-constrained null broadening beamforming algorithm offers superior performance in challenging noise environments.
• It provides an effective solution for maintaining anti-jamming capabilities in high-speed moving platforms.
• The algorithm enhances SINR and reduces waveform distortion, outperforming current methods.