Effectiveness Evaluation of Signals Consecutive Fusion
Abstract
The article deals with modeling and evaluating the effectiveness of sequential integration of signals from unequal information systems that measure the true signal. The signals of information systems were modeled as a harmonic signal with additive Gaussian noise, and the modeling process itself as a sequence of operations: generating a true signal, measuring it by an information system, receiving signals from the information system that go to the first fusion block, and optimal integration in the second fusion block. The first fusion block is an algorithm for calculating the weights of information systems signals, which take into account both the signal quality itself (the accuracy of measuring the true signal) and the quality of the information systems themselves, which is due to the initial unequal accuracy of the latter. The second fusion block is an optimal algorithm for processing the signals weighted in the first block, using the least squares method to obtain the total signal fusion. Since the process of measuring a quantity is of a statistical nature, 1000 realizations of measurement were simulated to evaluate the effectiveness. Modeling has shown the effectiveness of the proposed approach: if the accuracy of the fusioned signal after the first block fluctuates about 30%, then the gain from using also the optimal fusion allows increasing the gain on average to 82.
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