scholarly journals 3D Body Scanning Measurement System Associated with RF Imaging, Zero-padding and Parallel Processing

2016 ◽  
Vol 16 (2) ◽  
pp. 77-86 ◽  
Author(s):  
Hyung Tae Kim ◽  
Kyung Chan Jin ◽  
Seung Taek Kim ◽  
Jongseok Kim ◽  
Seung-Bok Choi
Keyword(s):  
Signal Processing ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Measurement System ◽  
High Speed ◽  
Peak Frequency ◽  
Processing Unit ◽  
Zero Padding ◽  
Scanning Time ◽  
Rf Antenna

Abstract This work presents a novel signal processing method for high-speed 3D body measurements using millimeter waves with a general processing unit (GPU) and zero-padding fast Fourier transform (ZPFFT). The proposed measurement system consists of a radio-frequency (RF) antenna array for a penetrable measurement, a high-speed analog-to-digital converter (ADC) for significant data acquisition, and a general processing unit for fast signal processing. The RF waves of the transmitter and the receiver are converted to real and imaginary signals that are sampled by a high-speed ADC and synchronized with the kinematic positions of the scanner. Because the distance between the surface and the antenna is related to the peak frequency of the conjugate signals, a fast Fourier transform (FFT) is applied to the signal processing after the sampling. The sampling time is finite owing to a short scanning time, and the physical resolution needs to be increased; further, zero-padding is applied to interpolate the spectra of the sampled signals to consider a 1/m floating point frequency. The GPU and parallel algorithm are applied to accelerate the speed of the ZPFFT because of the large number of additional mathematical operations of the ZPFFT. 3D body images are finally obtained by spectrograms that are the arrangement of the ZPFFT in a 3D space.

scholarly journals Design of High Speed FFT using Urdhva-Tiryagbhyam Algorithm and Karatsuba Algorithm

2020 ◽  
Vol 9 (4) ◽  
pp. 1904-1908
Keyword(s):  
Image Processing ◽  
Signal Processing ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Execution Time ◽  
Communication Systems ◽  
High Speed ◽  
Floating Point ◽  
Calculation Algorithms ◽  
Floating Point Number

In gift scenario each method has to be compelled to be quick, adept and simple. Fast Fourier transform (FFT) may be a competent algorithmic program to calculate the N purpose Discrete Fourier transform (DFT).It has huge applications in communication systems, signal processing and image processing and instrumentation. However the accomplishment of FFT needs immense range of complicated multiplications, therefore to create this method quick and simple. It’s necessary for a number to be quick and power adept. To influence this problem the mixture of Urdhva Tiryagbhyam associate degreed Karatsuba algorithmic program offers is an adept technique of multiplication [1]. Vedic arithmetic is that the aboriginal system of arithmetic that includes a distinctive technique of calculation supported sixteen Sutras. Using these techniques within the calculation algorithms of the coprocessor can reduce the complexness, execution time, area, power etc. The distinctiveness during this project is Fast Fourier Transform (FFT) style methodology exploitation mixture of Urdhva Tiryagbhyam and Karatsuba algorithmic program based mostly floating point number. By combining these two approaches projected style methodology is time-area-power adept [1] [2]. The code writing is completed in verilog and also the FPGA synthesis on virtex 5 is completed using Xilinx ISE 14.5.

scholarly journals High Speed RADIX-2 Butterfly Structure Using Novel Wallace Multiplier

2018 ◽  
Vol 7 (3.4) ◽  
pp. 213
Author(s):  
Garima Thakur ◽  
Harsh Sohal ◽  
Shruti Jain
Keyword(s):  
Signal Processing ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
High Speed ◽  
Arithmetic Units

In Signal Processing applications the arithmetic units mainly consists of adders and multipliers. These arithmetic units are used in to enhance the performance of Fast Fourier Transform (FFT) Butterfly structure implementation. This paper discusses the addition and multiplication algorithms for parameters like speed, area and power. The best suited among all adders are Kogge Stone Adder (KSA) while among multipliers are Wallace multiplier(WM) which is used for the implementation of the FFT structure. Verilog coding is used for implementation of circuit and the tool used is Xilinx ISE 14.1 Design suite. 

The whole can be very much less than the sum of its parts

2019 ◽  
Vol 103 (556) ◽  
pp. 117-127
Author(s):  
Peter Shiu
Keyword(s):  
Signal Processing ◽  
Fourier Transform ◽  
Mr Imaging ◽  
Fast Fourier Transform ◽  
Data Compression ◽  
Mobile Phones ◽  
Processing Data ◽  
Speed Up ◽  
Indispensable Tool ◽  
Computing Machines

This Article is on the discrete Fourier transform (DFT) and the fast Fourier transform (FFT). As we shall see, FFT is a slight misnomer, causing confusion to beginners. The idiosyncratic title will be clarified in §4.Computing machines are highly efficient nowadays, and much of the efficiency is based on the use of the FFT to speed up calculations in ultrahigh precision arithmetic. The algorithm is now an indispensable tool for solving problems that involve a large amount of computation, resulting in many useful and important applications: for example, in signal processing, data compression and photo-images in general, and WiFi, mobile phones, CT scanners and MR imaging in particular.

The fast Fourier transform

2020 ◽  
pp. 134-189
Author(s):  
Rob H. Bisseling
Keyword(s):  
Signal Processing ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Weather Forecasting ◽  
Data Access ◽  
Regular Pattern ◽  
Matrix Products ◽  
Data Redistribution ◽  
Fft Algorithms ◽  
Matrix Vector

This chapter demonstrates the use of different data distributions in different phases of a parallel fast Fourier transform (FFT), which is a regular computation with a predictable but challenging data access pattern. Both the block and cyclic distributions are used and also intermediates between them. Each required data redistribution is a permutation that involves communication. By making careful choices, the number of such redistributions can be kept to a minimum. FFT algorithms can be concisely expressed using matrix/vector notation and Kronecker matrix products. This notation is also used here. The chapter then shows how permutations with a regular pattern can be implemented more efficiently by packing the data. The parallelization techniques discussed for the specific case of the FFT are also applicable to other related computations, for instance in signal processing and weather forecasting.

Application of Chirp-z Transform in Doppler Weather Radar

2014 ◽  
Vol 513-517 ◽  
pp. 4265-4268
Author(s):  
Jun Zhu ◽  
Xiao Jia Lu ◽  
Xiang Liu
Keyword(s):  
Signal Processing ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Measurement Accuracy ◽  
Weather Radar ◽  
Doppler Weather Radar ◽  
Transform Method ◽  
Fast Fourier Transform Method ◽  
Sampling Points ◽  
Signal Processing Methods

Among the signal processing methods of Doppler weather radar, the FFT (Fast Fourier Transform) method is widely used. If the measurement accuracy needs to be improved, the number of FFT points also needs to be increased. As a result, the amount of computation increases exponentially. Chirp-z transform can directly refine certain spectrum in the spectrum of weather echoes. In the case that the sampling points and the amount of computation increase fewer, the measurement accuracy can be greatly advanced.

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