A new approach to Fourier analysis of randomly sampled data using linear regression technique

A literature survey of spectrum analysis techniques for randomly sampled records shows that most are unsuitable for real time applications and require considerable high speed storage. A simple approach to spectrum estimation from randomly sampled records has been attempted. The algorithm is based upon the Fourier series and the method of least squares. Example results from both simulated and experimental data are presented.