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<p>This paper introduces a novel method for reducing errors in communication systems impacted by single and multiple knife-edge and dielectric wedge diffraction losses across fixed and variable frequencies, using a Kalman filter. New diffraction loss formulae for dielectric wedges have been developed. Diffraction phenomena, common in wave propagation, often cause significant signal degradation. By applying the Kalman filter, we can recursively estimate these losses, improving the accuracy of signal strength predictions. A detailed computational complexity analysis is presented, demonstrating that the Kalman filter operates with an optimized complexity of <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(O\left({n}^{2}\right)\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>O</mi> <mfenced close=")" open="("> <msup> <mrow> <mi>n</mi> </mrow> <mn>2</mn> </msup> </mfenced> </mrow> </math></EquationSource> </InlineEquation>, making it feasible for real-time diffraction loss estimation. The complexity of multi-obstacle diffraction modeling is also analyzed, showing a linear scaling of <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(O(n)\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>O</mi> <mo stretchy="false">(</mo> <mi>n</mi> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation> per obstacle. Comparative analysis with alternative methods, such as ray-tracing and empirical models, highlights the efficiency of the Kalman-based approach. Our results show that the Kalman filter effectively reduces noise, aligning diffraction loss estimates with theoretical predictions and enhancing system reliability in environments with both single and multiple obstacles. Additionally, a BPSK-modulated system with Hamming (7, 4) error correction is analyzed, demonstrating the Kalman filter’s capability to bring received symbols closer to their transmitted positions in the constellation diagram, significantly improving the bit error rate.</p>

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Innovative Kalman Filtering Approach for Compensating Diffraction Losses in Communication Systems

  • 期刊论文

  • 发表日期：

    2025年5月11日

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  • Vinod Kumar

摘要

This paper introduces a novel method for reducing errors in communication systems impacted by single and multiple knife-edge and dielectric wedge diffraction losses across fixed and variable frequencies, using a Kalman filter. New diffraction loss formulae for dielectric wedges have been developed. Diffraction phenomena, common in wave propagation, often cause significant signal degradation. By applying the Kalman filter, we can recursively estimate these losses, improving the accuracy of signal strength predictions. A detailed computational complexity analysis is presented, demonstrating that the Kalman filter operates with an optimized complexity of \(O\left({n}^{2}\right)\) O n 2 , making it feasible for real-time diffraction loss estimation. The complexity of multi-obstacle diffraction modeling is also analyzed, showing a linear scaling of \(O(n)\) O ( n ) per obstacle. Comparative analysis with alternative methods, such as ray-tracing and empirical models, highlights the efficiency of the Kalman-based approach. Our results show that the Kalman filter effectively reduces noise, aligning diffraction loss estimates with theoretical predictions and enhancing system reliability in environments with both single and multiple obstacles. Additionally, a BPSK-modulated system with Hamming (7, 4) error correction is analyzed, demonstrating the Kalman filter’s capability to bring received symbols closer to their transmitted positions in the constellation diagram, significantly improving the bit error rate.