Efficiency comparison of quasi-optimum direction finding algorithms used for point sources of signals

Two quasi optimum direction finding algorithms based on the Markov theory of optimal nonlinear filtration are compared with respect to efficiency. The algorithm of time processing in the Gaussian approximation for signals mixed with additive stationary white noise and the algorithm of spacetime processing for signals mixed with uniform in space white noise are investigated. The radiation pattern of a direction finder is used as basis for comparative evaluation of the algorithms. Calculation of the error dispersion in each algorithm and of the convergence rate of each as function of the signal to noise ratio reveals that the second algorithm becomes increasingly more efficient than the first one as the signal to noise ratio decreases.