The JM-Filter to Detect Specific Frequency in Monitored Signal (original) (raw)
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IEEE Transactions on Instrumentation and Measurement, 2019
In this paper, design of frequency-locked loop (FLL) is proposed based on computationally efficient DFT structures. In recent years, the DFT structures are evolved as sliding DFT, modulated sliding DFT, hopping DFT, modulated hopping DFT, and sliding windowed infinite Fourier transform. Considering their tuned filter characteristics, an attempt has been made to obtain a solution for the instantaneous frequency estimation problem of the input signal under varying center frequency condition. In each DFT structure, the k th bin in-phase and quadrature components are separated for instantaneous signal extraction. The feedback loop is designed around these DFT structures and it was observed that the frequency responses exhibit flat magnitude and phase interestingly, when compared to the open-loop structures. Hence, an adaptive sampling frequency adjustment scheme is proposed for these structures as frequency locked-loop to estimate the instantaneous frequency of the input signal for wide variation in center frequency. These FLLs with different DFT structures are tested for dynamic performance and wide operating range. The proposed FLLs are implemented in FPGA and experimental investigations have been carried out for frequency estimation. Further experimental investigations on these FLLs as system on chip were carried out with area and power analysis. Index Terms-Discrete Fourier transform, FPGA, frequencylocked loop, hopping discrete Fourier transform, modulated discrete Fourier transform, modulated hopping discrete Fourier transform, sliding discrete Fourier transform, system on chip.
An accurate Dual Tone Multiple Frequency Detector based on the low-complexity Goertzel algorithm
2001
This article presents a low complexity dual tone multiple frequency (DTMF) signal detector that meets the International Telecommunication Union (ITU) Q.24 DTMF standard while implemented on a general purpose Digital Signal Processor (DSP). The proposed DTMF detector is based on the Goertzel algorithms and is well suited for a multichannel implementation. Our solution offers increased accuracy and noise margins, while preserving the inherited advantages of the Goertzel algorithm (less memory requirements and computational complexity).
2006 IEEE Midwest Symposium on Circuit and Systems, 2006
It is well known that the discrete Short Time Fourier Transform (STFT) can be considered from the perspective of a Discrete Fourier Transform (DFT) taken over short time sections of the signal (the window is fixed) or from the perspective of a filtering operation at a given frequency (the frequency is fixed). We have proposed a mixed approach where the spectrum of each finite short time section of the signal is estimated by realizing a DFT through a bank of IIR Goertzel Filters centered at the specified frequencies. This approach allows computing the time varying spectrum at precisely the frequencies of interest. The Goertzel algorithm can be adjusted to implement the Nonuniform Discrete Fourier Transform (NDFT). Within the NDFT framework the estimation of the spectrum at the desired frequency it is not conditioned to the requirement that the DFT index, k, be an integer. We have termed this implementation of the discrete STFT the "Nonuniform Discrete Short Time Fourier Transform" (NSTFT). A MATLAB program was written and validated using this technique, then the methods were compared for different windows size and different number of frequencies of interest, to a MATLAB FIR filtering view implementation.
Dtmf Detection Using Goertzel Algorithm
Dual-tone multi-frequency(DTMF) is an international signaling standard for telephone digits(number buttons). These signals are used in touch-tone telephones as well as many other areas. Since analog devices are rapidly changing with digital devices, digital DTMF decoders become more important. The subject of this paper is to build a dual-tone multi-frequency(DTMF) signal detector. There are many algorithms for DTMF detection, and among all of them the chosen one is Goertzel's algorithm. It is one of the simplest algorithms of all and it is very often used in practical realizations. The simulation of this algorithm is done in MATLAB and outputs of this test are given in this paper.
A Simple Recursive Algorithm for Frequency Estimation
IEEE Transactions on Instrumentation and Measurement, 2004
A new approach to the design of a digital algorithm for local system frequency estimation is presented. The algorithm is derived using the maximum likelihood method. One sinusoidal voltage model was assumed. FIR digital filters used in papers [11], [12] are used to minimize the noise effect and to eliminate the presence of the harmonics effect. The algorithm showed a very high level of robustness as well as high measurement accuracy over a wide range of frequency changes. The algorithm convergence provided fast response and adaptability. This technique provides accurate estimates with error in the range of 0.005 Hz in about 25 ms and requires modest computations. The theoretical basis and practical implementation of the technique are described. To demonstrate the performance of the developed algorithm, computer simulated data records are processed.
IEEE Transactions on Instrumentation and Measurement, 1998
An intelligent FFT-analyzer capable of adapting its operating parameters on the basis of the signal spectrum was set up and characterized. The realized instrument is based on a parameter optimization procedure which provides the instrument an autoconfiguration capability. It was implemented on a multiple processor DSP architecture in order to achieve a real-time behavior. The experimental tests carried out on a large number of signals highlight the instrument capability of correctly detecting tones with a good frequency resolution for any signal spectrum type. ).
A Comparative Study on Discrete Fourier Transformation for Digital Signal Analysis
2019
In this article, the basic information on discrete signals, discrete Fourier series, discrete Fourier transformation and their computational implement of signal processing system are described. Now a day, digital signal processing (DSP) is an important research topic because it significantly increases the overall value of hearing protection. From millions of signals, DSP suppresses noise without blocking the speech signal easily. Again without compromising communication, DSP systems protect the users from unhealthy noise exposure. This study addressed some mathematical and graphical techniques for discrete signals reconstruction by using Discrete Fourier Transformation (DFT). DFT is one of the most popular analyzed techniques for DSP system. In this work, we will try to separate the input signal into the real and imaginary part by using DFT algorithm in MATLAB. On the other hand, we will try to reconstruct the given discrete signal with the help of MATLAB program with graphical representation. 1. Introduction Now a day, signal reconstruction from partial Fourier domain information has been interesting to a number of different authors both for particular applications and for its inherent theoretical value [1]. Previous work in this area has involved developing conditions under which signals are uniquely specified with Fourier transform magnitude or phase [2] or signed magnitude information and developing practical algorithms for recovering signals from this information. In this paper, we consider the problem of reconstructing signals from only discrete Fourier transform (or inverse discrete Fourier transform) sign information [3]. By interpolated DFT method with maximum sidelobe decay windows, a multi-frequency signal was analyzed [4]. Again, to improve the accuracy of periodic signal analysis another algorithm was performed [5]. This proposed approach required quite modest additional computational burden which make it suitable for real-time signal professing. Firstly, they showed that how the proposed method can be used in the case of DFT analysis of harmonic signals, and secondly, it was considered that the digital wattmeter application area in electrical power-system measurement. To analyze the exponential signal by the interpolated DFT algorithm another method was described [6]. In [7], DFT algorithm analyzed in low-cost power quality measurement systems based on a DSP processor.
Efficient FM demodulation by single tone detection for FPGA implementation
2005
This paper presents a software radio receiver architecture that uses a single tone detection technique to demodulate a frequency modulated (FM) signal. In a software radio most of the signal processing algorithms are performed in software or in digital hardware instead of using analogue components. A conventional software radio receiver uses filters to demodulate FM signals. The Fourier Transform can also be used to demodulate FM signals. The presented single tone detection software radio (STDSR) uses the Goertzel Algorithm as a single bin discrete Fourier Transform to detect if a particular frequency is present in an FM signal. The STDSR is used to demodulate a commercial FM radio station audio signal. This paper compares the STDSR with filter based and Fast Fourier Transform (FFT) based software radios in terms of FPGA resource usage and computational efficiency. The STDSR was found to be more efficient to implement than the filter or FFT based software radios. Future work includes improving the audio signal quality and applying the STDSR architecture to other wireless modulation and demodulation methods.
Non-Uniform Discrete Short-Time Fourier Transform A Goertzel Filter Bank Approach
2004
It is well known that the discrete Short Time Fourier Transform (STFT) can be considered from the perspective of a Discrete Fourier Transform (DFT) taken over short time sections of the signal (the window is fixed) or from the perspective of a filtering operation at a given frequency (the frequency is fixed). The latter approach is typically useful when only a few frequencies of interested are required or when the window used to segment the data has infinite length. For such windows the implementation requires a bank of recursive filters (IIR). When finite length windows are used, the bank of filters is non-recursive (FIR). In such case the use of a suitable approximation by IIR filters could eventually reduce the computational cost. We are proposing a mixed approach where the spectrum of each finite short time section of the signal is found by realizing a DFT through a bank of IIR Goertzel Filters centered at specified frequencies. This approach allows computing the time varying spectrum at precisely the frequencies of interest. In fact, the Goertzel algorithm is used to implement the Non-Uniform Discrete Fourier Transform (NDFT). Within the NDFT framework the estimation of the spectrum at the frequency of interests it is not conditioned to the requirement that the DFT index, k , be an integer. We have termed this implementation of the discrete STFT the "Non-Uniform Discrete Short Time Fourier Transform" (NSTFT). A MATLAB program was written using this technique and validated. Future work includes computational cost analysis, synthesis issues and a viability study regarding the use of the so-called Sliding Goertzel DFT for the implementation of a discrete STFT.
DIGITAL SIGNAL PROCESSING TECHNIQUE FOR RECOGNITION OF DUAL TONE MULTI FREQUENCY SIGNALING
Digital signal processing techniques for obtaining high accuracy in recognition of dual-tone multi-frequency signaling(DTMF) tones produced by the push buttons of the keypad of a traditional analog telephone which was a major consequence these days. In order to avoid that, the proposed methodologies employ a suitable computations to analyze one selected frequency component from a discrete signal[2][3]. A complete meteorological characterization of the methods, in terms of systematic and random errors, is achieved, demonstrating the high overall performance. Keywords: DTMF, FFT, discrete signal, DFT, digital filter.