Improving the Efficiency of Inverse Signal Filtering by Basis Correction Method

Introduction. Enhancing the resolution of radar stations beyond the Rayleigh limit is particularly important for modern radio electronic systems operating under conditions of low signal-to-noise ratios and intense external interference. This task becomes crucial for ensuring accurate detection and identification of objects at significant distances, which extend possibilities for applying this technology. Inverse filtering (IF) is an effective processing method; however, in standard cases, its efficiency depends significantly on the noise environment, limiting its application in real-world scenarios.

Aim. Development and investigation of an approach aimed at enhancing IF efficiency by introducing a basis correction method, which improves signal processing quality and increases system robustness to interference.

Materials and methods. The research was carried out using the methods of mathematical simulation of filtering processes and analysis of the influence of various parameters on the IF efficiency. Simulation studies were conducted in a specially developed software environment. The methods of signal processing theory, including matrix theory and probability theory, were used.

Results. A method of basis correction is proposed, which increases the efficiency of IF by increasing the signal-tonoise ratio at the filter output. Dependencies of the signal-to-noise ratio on correction parameters are obtained. The concept of the mean square of the filter's impulse response norm is introduced, providing an additional analytical tool for evaluating and optimizing the method. A practical approach for implementing the method to enhance the resolution of radar systems is proposed.

Conclusion. The basis correction method improves the efficiency of IF and extends its application capabilities in the conditions of a low input signal-to-noise ratio. The research significance consists in the development of a novel methodology for improving signal processing quality in radar systems, which extends their applicability under adverse signal reception conditions.

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