C Program for Spherical Azimuth Angle Algorithm and Related Signal Processing Methods

Resource Overview

A collection of C and MATLAB algorithms for signal processing and communications. Features spherical azimuth calculation (azimuth.cpp), fast CRC checksum implementation (CRC_Table.cpp), descrambling algorithm (scrambler.cpp), MATLAB signal bandwidth measurement (BandWith.m), bandpass signal down-conversion (fqmv.m), QPSK demodulation (demodQpsk.m), Welch power spectral density estimation (psdwh.m), mean filtering (cvmn.m), and signal orthogonal decomposition (Cnv2Bas.m). Each implementation includes optimized code structures and mathematical foundations.

Detailed Documentation

The original content has been expanded with additional details while preserving core concepts: C program for spherical azimuth angle calculation: azimuth.cpp - Implements coordinate transformation algorithms using trigonometric functions to compute azimuth angles on spherical surfaces. Fast CRC checksum algorithm: CRC_Table.cpp - Utilizes precomputed lookup tables for efficient cyclic redundancy check calculations, significantly improving processing speed. Descrambling algorithm: scrambler.cpp - Employs XOR operations with pseudo-random sequences to recover original data from scrambled signals. MATLAB program for signal bandwidth measurement: BandWith.m - Calculates signal bandwidth using frequency domain analysis and threshold-based detection methods. Bandpass signal down-conversion: fqmv.m - Implements heterodyne mixing and filtering techniques to translate bandpass signals to baseband. QPSK demodulation: demodQpsk.m - Performs quadrature phase-shift keying demodulation through carrier recovery, phase detection, and symbol decision mechanisms. Welch algorithm for power spectral density estimation: psdwh.m - Applies windowed periodogram averaging with overlap-add processing for robust spectral analysis. Mean filtering algorithm: cvmn.m - Implements sliding-window averaging operations for noise reduction and signal smoothing. Signal orthogonal decomposition: Cnv2Bas.m - Transforms signals into orthogonal components using basis projection methods like Fourier or wavelet transforms. These additional implementations provide comprehensive coverage of fundamental signal processing operations while maintaining the original technical specifications.