Beamforming Visualization for Planar Arrays with Code Implementation
Comprehensive beamforming visualization techniques and implementation code for planar arrays, featuring contour plots, polar 3D diagrams, and MATLAB/Python simulation examples
Beamforming Capon Algorithm Simulation for Array Signal Processing
Array Signal Processing Capon Algorithm Beamforming Simulation: This program implements Capon's minimum variance distortionless response (MVDR) beamformer with N array elements and K sampling points. The desired signal arrives at 30 degrees while an interfering signal impinges from 60 degrees. Key functionality: extract desired signals while suppressing interference through optimal weight vector computation.
MT-LSCMA Intelligent Antenna Beamforming Blind Adaptive Improved Algorithm
MT-LSCMA Intelligent Antenna Beamforming Blind Adaptive Improved Algorithm with Code Implementation Insights
Simulation Study on Unambiguous and Ambiguous Sectors in Beamforming
A comprehensive simulation analysis of unambiguous and ambiguous sectors in beamforming with accompanying multi-beam formation program code. Note: All uploaded code represents original algorithms developed through long-term professional work, featuring phased array implementation and sector ambiguity resolution techniques.
Adaptive Beamforming Algorithms for Smart Antennas
Research and implementation of adaptive beamforming algorithms for smart antennas, featuring improvements to fundamental algorithms and computational methods, with code implementation insights for enhanced learning and practical applications.
Application of Least Mean Square (LMS) Algorithm in Beamforming
Implementation of Least Mean Square (LMS) Algorithm in Beamforming Systems - LMS Algorithm Steps: 1. Variable and Parameter Definition: X(n) as input vector/training sample, W(n) as weight vector, b(n) as bias term, d(n) as desired output, y(n) as actual output, η as learning rate, n as iteration count. 2. Initialize weight vector W(0) with small random non-zero values, set n=0. 3. For input samples x(n) and desired output d, compute: e(n)=d(n)-X^T(n)W(n) followed by weight update W(n+1)=W(n)+ηX(n)e(n). 4. Check convergence criteria - terminate if satisfied, otherwise increment n and return to step 3. The algorithm demonstrates adaptive filter implementation for real-time beam pattern optimization.
Simulation Program for Wideband Time-Delay Beamforming
A comprehensive simulation program for wideband time-delay beamforming, featuring clear implementation with commented code examples ideal for beginners. Includes practical demonstrations of delay calculation algorithms and beam pattern visualization techniques.
Sonar Array Receive Beamforming
MATLAB-based sonar array receive beamforming implementation focusing on horizontal plane beamforming with signal processing algorithms
Beamforming Techniques for Acoustic Source Localization
Microphone Array-Based Sound Source Localization with Implementation Approaches
Linear, Planar, and Circular Array Radiation Patterns
Fundamentals of antenna array radiation patterns including linear arrays, planar arrays, and circular arrays with code implementation insights