Coherent combination of signals from diverse sensors

We consider a the problem of coherently combining signals having several sinusoidal components as measured via multiple sensors, in which each sensor has its own transfer function. It is desirable to combine the sensor outputs to improve the signal-to-noise ratio, but simply co-adding the signals could result in signal cancellation, due to phase changes in the sensors. We propose here a combining architecture which blindly adjusts the phases of the signals to maximize signal output. Different combining filters are considered: an allpass filter, and FIR filters designed according to a maximum SNR and minimum mean-squared error constraint. The allpass filters are trained both via steepest ascent and simplex optimization. The allpass combining filters provide excellent SNR improvement, while preserving all the frequency components.