Comparative Performance Analysis of Three Sub-Optimal Projection Techniques for Multidimensional Signal Detection

The paper derive the projection method which a set of samples is represented by a single sample, it maximizes the probability of signal detection for a fixed probability of false alarm and solve the cumbersome of multidimensional signal detection, The focus of the paper is performance analysis of three sub-optimal projection techniques (maximum value projection, summation projection and the probabilistic weighted summation projection) for multidimensional signal detection, there are pros and cons respectively by running Monte-Carlo simulations and analysis the losses of projection algorithms, The paper obtains the theory and the simulation results which are useful to realize optimize multidimensional signal detection.