Estimation of Phase Difference in Multiple Sensor Arrays

The likelihood functional for estimating parameter differences in coherent multiple-sensor receivers is developed assuming Gaussian statistics on both signal and noise. The development relies on a matrix formulation and a subsequent factorization of a parameter constraint matrix from the signal matrix. A two-antenna phase-difference radar example is presented for cases of uncorrelated and antenna-correlated noise.     

Quantization of PMT Signals for Meteorological Satellites

Quantization rules are examined for a satellite radiometer in the visual range. Effects of photomultiplier tube (PMT) noise on the detection of cloud brightness levels are of particular interest because the expected radiance levels are high. Effects of area integration are considered to improve the probability of detection at high radiance levels.     

Phase Analysis in Multiple-Sensor Receivers with High Signal-to-Noise Ratio

The ideal phase detector characteristic is analyzed for estimating the phase difference between two stochastic input signals. This can essentially be described as a correlation process formed by multiplying the two input signals and extracting the phase. High signal-to-noise ratio conditions are assumed to linearize the system with respect to the noise. The effects of the nonlinearity on the signal are handled in terms of a series expansion and by using low-pass filtering on the receiver output. The mean square error of the system is calculated for some typical parameters.