Abstract :
In dealing with narrowband noise processes the density p(R1 ,R2,Δ) in which R1 and R2 are envelope samples and Δ is the phase difference can play an important role in determining system design features such as diversity performance, crossing rates, error probabilities, optimum processing and frequency or phase distributions. Standard texts on signal detection or radar usually include a discussion of p(R) and, less often, of p(R1 ,R2) but the number of instances in which p(R1 ,R2,Δ) can be specified is limited, and here known results are touched upon while a general form for this joint density is developed. The work extends an earlier treatment of p(R1 ,R2,Δ) and includes some important observations regarding the method used here and a SIRP (spherically invariant random process) approach which has been widely proposed for the analysis of correlated radar returns. Two differing families of non-Gaussian processes are used to illustrate the working and a number of densities for the jointly correlated pair R1 and R2, and the phase difference Δ are given, so extending the pool of such results available to the analyst. The approach used is heuristic and although the positivity of p(Δ) is not proven outright, experience and the cases illustrated point to this requirement being met
Keywords :
backscatter; correlation methods; noise; probability; radar cross-sections; radar signal processing; random processes; signal detection; backscatter; correlated radar returns; crossing rates; digital radio systems; diversity performance; envelope samples; error probabilities; frequency distribution; heuristic method; joint phase and envelope densities; narrowband noise processes; non-Gaussian processes; optimum processing; phase difference; phase distribution; signal detection; spherically invariant random process; system design;