Fast parameter estimation algorithms for linear FM signals

This paper describes computationally efficient algorithms for estimating the parameters of a complex linear FM signal in white Gaussian noise. Algorithm I deals with the high signal to noise ratio (SNR) case (above -4 dB for asymptotically long signals). Algorithms II and III are for the low SNR range. Algorithm II is based on the maximum likelihood (ML) approach, but takes advantage of the numerical conditioning of the parameter estimation problem to yield a computationally efficient algorithm. Algorithm III also has its roots in the ML procedure, but uses a suboptimal implementation to avert the difficult 2D search procedure. Simulations are provided to illustrate performance.<>