Low‐pass filter for the DFT process and its application to impulse response of sound‐field and ultrasonic B‐mode echo simulator

We have developed a Kalman filter to estimate accurate Eötvös corrections and horizontal ship accelerations from Global Positioning System (GPS) fixes. High‐resolution shipboard gravity measurements are obtained with a newly designed, linear phase, Finite Impulse Response (FIR) low‐pass filter. Both filters are combined to yield accurate, near‐real time, Eötvös‐corrected underway gravity estimates. Error ranges that reflect uncertainty in navigation for these estimates are calculated from autocovariances of Kalman velocity estimates by means of variance propagation expressions for time‐invariant linear digital filters. Estimates of horizontal ship acceleration are combined with a simplified instrument impulse response model in an attempt to remove transient noise from the gravimeter output. We apply the technique to data collected by two shipboard gravimeters, a LaCoste & Romberg Model S Air‐Sea Gravity Meter and a Bell Aerospace BGM-3 Marine Gravity Meter System, operated side‐by‐side on the Scripps R/V Thomas Washington during Leg 1 of the Roundabout expedition. In the absence of significant horizontal accelerations due to course or speed changes, both instruments yield data with good repeatability, characterized by rms differences of less than 1 mGal. Horizontal accelerations generate transient signals that cannot be modeled at present to an accuracy of better than 5 mGal. Difficulties in removing these transients are primarily due to insufficient quantitative knowledge of the response of the instrument, including the gyro‐stabilized platform. This can be determined analytically or empirically.

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Convolution Integral: How a Graphical Type of Solution Can Help Minimize Misconceptions

Journal of Electrical And Electronics Engineering ◽

10.33021/jeee.v3i2.1489 ◽

2021 ◽

Vol 3 (2) ◽

pp. 103

Author(s):

Hendra J. Tarigan

Keyword(s):

Impulse Response ◽

Physical System ◽

Convolution Integral ◽

Pass Filter ◽

Low Pass Filter ◽

Convolution Integrals ◽

Low Pass ◽

Simulation And Experiment ◽

Rc Circuit ◽

Set Up

A physical system, Low Pass Filter (LPF) RC Circuit, which serves as an impulse response and a square wave input signal are utilized to derive the continuous time convolution (convolution integrals). How to set up the limits of integration correctly and how the excitation source convolves with the impulse response are explained using a graphical type of solution. This in turn, help minimize the students’ misconceptions about the convolution integral. Further, the effect of varying the circuit elements on the shape of the convolution output plot is presented allowing students to see the connection between a convolution integral and a physical system. PSpice simulation and experiment results are incorporated and are compared with those of the analytical solution associated with the convolution integral.

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A hybrid window function to design finite impulse response low pass filter with an improved frequency response

2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS) ◽

10.1109/icecds.2017.8389684 ◽

2017 ◽

Author(s):

D. Kalaiyarasi ◽

T. Kalpalatha Reddy

Keyword(s):

Frequency Response ◽

Impulse Response ◽

Finite Impulse Response ◽

Window Function ◽

Pass Filter ◽

Low Pass Filter ◽

Low Pass

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Computing efficiency of the three-stage interpolated low pass filters

Radio Industry (Russia) ◽

10.21778/2413-9599-2018-28-4-21-27 ◽

2018 ◽

Vol 28 (4) ◽

pp. 21-27

Author(s):

I. S. Savinykh ◽

D. A. Chemasov

Keyword(s):

Impulse Response ◽

Computational Efficiency ◽

Finite Impulse Response ◽

Sampling Rate ◽

Efficiency Coefficient ◽

Transition Band ◽

Pass Filter ◽

Low Pass Filter ◽

Low Pass ◽

Low Pass Filters

Undoubted advantages of finite impulse response filters are their unconditional stability, the absence of limit cycles and the possibility of implementing a filter that does not introduce phase distortion. The disadvantage of such filters is the large cost required to compute the response. This paper considers three-stage interpolated finite impulse response low-pass filters. The maximum values of the interpolation factors are determined. Dependences of the coefficient of computational efficiency and the coefficient of increase in the registers of the three-stage interpolated low-pass filter on the values of the interpolation factors, the widths of the passband and the transition band are obtained. Relations for determining the optimal values of interpolation factors corresponding to the maximal value of computational efficiency coefficient are obtained. In addition, the dependencies of the maximum coefficient of computational efficiency and the optimal coefficient of increase in the registers of the three-stage interpolated low-pass filter on the widths of the passband and the transition band at the optimum values of the interpolation factors are obtained. Considered three-stage interpolated low-pass filters should be used in the case when the required stopband is significantly less than the sampling rate. In this case, three- stage interpolated filters require less computational resources for calculating the response than the two-stage interpolated filters or filter implemented by the transversal structure.

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