Optimized weighted averaging of peak matched multiple window spectrum estimates

Periodogram averaging with multiple windows can be used in spectrum analysi s of nonstationary data. Usually, however, the windows for the subspectra a re equally weighted in the estimate. In this correspondence, a criterion fo r the optimization of weighting factors is formulated as the average of nor malized bias, variance, or mean square error in a certain frequency interva l around a predefined peaked spectrum. The weighting factors are optimized using the peak matched multiple windows, the sinusoid multiple windows, and the discrete prolate spheroidal sequences.