Moving and stationary target acquisition radar image enhancement through polynomial windows

The Fourier transform involved in synthetic aperture radar (SAR) imaging causes undesired sidelobes which obscure weak backscatters and affect the image clarity. These sidelobes can be suppressed without deteriorating the image resolution by smoothing functions known as windowing or apodization. Recently, the theory of orthogonal polynomials has gained considerable attention in signal processing applications. The window functions that are derived from the orthogonal polynomials have interesting sidelobe roll-off properties for better sidelobe apodization, hence it can be used for radar image enhancement. In this work, a new window is constructed from Jacobi orthogonal polynomials and its performance in SAR imaging is analyzed and compared with commonly used window functions. Also, apodization functions involved in Fourier transform harmonic analysis and Fourier transform spectroscopy are discussed in the context of SAR imaging

FIR Filter Design using Raised Semi-ellipse Window Function

In this paper, a new two-parameter window function - Raised semi-ellipse (RSE) is proposed. The window is obtained from a fixed elliptical window known as Semi-ellipse window by raising the radius of the minor axis by the parameter (β), and applied for the design of finite impulse response (FIR) digital filters. The spectral parameters of the proposed window are determined first and compared with the Kaiser window – a 2-parameter adjustable window. Subsequently, in its application in filter design with an established design algorithm, the newly proposed adjustable window is compared to the Semi-ellipse window to examine its improvement and also the Kaiser window to compare its performance with a commonly used adjustable window. The filter simulation results show that the filters designed with the proposed window can provide more reduced ripples than the Kaiser window for prescribed spectral characteristics

Design of FIR digital filters using Semi-ellipse window

A fixed window function which is similar in shape to a semi-ellipse is proposed. The semi–ellipse which has its major axis to be equal to the window length and the minor axis at unity produced about 4.2 dB lower ripple ratio than the rectangular window. The proposed window function is derived from the equation of an ellipse in the explicit and parametric forms. First of all, the spectral characteristic of the proposed window is studied in terms of spectral parameters and compared with other fixed windows like Rectangular, Bartlett, Hann, Hamming and Blackman windows. The window simulation results reveal that the proposed window produced comparable spectral characteristic with existing standard fixed windows. Secondly, the paper presents the application of the proposed window in a digital filter design. The filter analysis comparison results with other fixed windows namely Bartlett, Von Hann, Hamming, and Kaiser window, an adjustable window, confirm that filter design with the proposed window exhibits good spectral characteristic, and can be used to design better filter than the Bartlett window using less than half the Bartlett’s filter length for a fixed transition width. The similicity of its coefficients formulation and design algorithm makes it a good choice for digital filter design applications

Adapted raised cosine window function for array factor control with dynamic range ratio limitation

The use of window functions to improve the side lobe level of antenna arrays is hindered by high value of excitation currents dynamic range ratio. This paper proposes a fast and iterative window function generation strategy aimed at achieving improved side lobe level starting from a preset current dynamic range ratio. Based on this strategy a new window function is developed for standard set of conditions.info:eu-repo/semantics/publishedVersio

Window Functions and Their Applications in Signal Processing

Window functions—otherwise known as weighting functions, tapering functions, or apodization functions—are mathematical functions that are zero-valued outside the chosen interval. They are well established as a vital part of digital signal processing. Window Functions and their Applications in Signal Processing presents an exhaustive and detailed account of window functions and their applications in signal processing, focusing on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing. Comprehensively reviewing previous research and recent developments, this book: Provides suggestions on how to choose a window function for particular applications Discusses Fourier analysis techniques and pitfalls in the computation of the DFT Introduces window functions in the continuous-time and discrete-time domains Considers two implementation strategies of window functions in the time- and frequency domain Explores well-known applications of window functions in the fields of radar, sonar, biomedical signal analysis, audio processing, and synthetic aperture rada

Window Functions and Their Applications in Signal Processing

Window functions—otherwise known as weighting functions, tapering functions, or apodization functions—are mathematical functions that are zero-valued outside the chosen interval. They are well established as a vital part of digital signal processing. Window Functions and their Applications in Signal Processing presents an exhaustive and detailed account of window functions and their applications in signal processing, focusing on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing. Comprehensively reviewing previous research and recent developments, this book: Provides suggestions on how to choose a window function for particular applications Discusses Fourier analysis techniques and pitfalls in the computation of the DFT Introduces window functions in the continuous-time and discrete-time domains Considers two implementation strategies of window functions in the time- and frequency domain Explores well-known applications of window functions in the fields of radar, sonar, biomedical signal analysis, audio processing, and synthetic aperture rada

Nuclear Reactor Doubling Time Calculation Using FIR Filter

AbstractIn nuclear reactor engineering, reactor doubling time is generally applied to indicate the change of power level and usually provided by a nuclear instrumentation system (NIS). In a digital NIS, current signal from neutron detector is pre-amplified and conditioned into voltage signal which is proportional to the power level of nuclear reactor, and then is acquired and processed by a digital computer in the NIS. The measurement noise contained in the acquired voltage signal will cause a lot of uncertainty in the reactor doubling time calculation result. In this paper, the sensitivity analysis of nuclear reactor doubling time calculation is investigated. A calculation algorithm of reactor doubling time for digital NIS is proposed based on FIR Filtering techniques, and two filtering schemas to calculation reactor doubling time are given based on the FIR filter. A Hard-In-Loop (HIL) experiment environment was built to verify the discussed calculation algorithm. The experimental results show that the calculation algorithm developed can suppress the influence of measurement noise on calculation result to recover the signal's original features, and can provide us with good on-line calculation result

スパース時間周波数表現に関する研究

早大学位記番号:新9160博士（工学）早稲田大

Annual Review of Progress in Applied Computational Electromagnetics

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