1-Wang-FR1020-IGARSS11.pptx
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1) The document proposes a method using the discrete fractional Fourier transform (DFRFT) to estimate target vibrations from synthetic aperture radar (SAR) imagery. 2) The method was tested on SAR data collected by the Lynx system of a stationary target vibrating at 5 Hz with an amplitude of 1.5 mm. 3) The DFRFT method successfully estimated the target's vibration frequency and reconstructed the time-varying vibration acceleration signal from the SAR data.
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Keywords: Wind profiler, wavelet transform, Fourier transform, clutter, signal processing
chandra shekhar_Unit 2 _Radar_ feb 4 2016
This document outlines a unit plan on radar communication. It includes sections on radar principles and applications, radar frequency bands, pulse-related terms, the radar range equation, duplexer and display systems, types of radar including pulse, CW, FMCW, MTI and secondary radar, landing systems including ILS and GCA, and an introduction to SONAR. Various radar concepts are defined and block diagrams of radar systems are provided with explanations. The unit plan allocates 1 hour for each sub-section and includes learning objectives.
Mimo radar detection in compound gaussian clutter using orthogonal discrete f...
This paper proposes orthogonal Discrete Frequency Coding Space Time Waveforms (DFCSTW) for
Multiple Input and Multiple Output (MIMO) radar detection in compound Gaussian clutter. The proposed
orthogonal waveforms are designed considering the position and angle of the transmitting antenna when
viewed from origin. These orthogonally optimized show good resolution in spikier clutter with Generalized
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Implementation of adaptive stft algorithm for lfm signals
Abstract
Normally Time-Frequency analysis is done by sliding a window through the time domain data and computing the Fourier
Transform of the data within the window. The choice of the window length determines whether specular or resonant information
will be emphasized. A narrow window will isolate specular reflections but will not be wide enough to accommodate the slowly
varying global resonances; a wide window cannot temporally separate resonance and specular information. So we will adapt
window length according to changes in frequencies. In this case we are realizing the specifications of Linear Frequency
Modulation (LFM) signal.
Index Terms—LFM, FFT, DFT, STFT and ASTFT.
Doppler radar
1. Doppler radar uses the Doppler effect to measure the radial velocity of targets. It transmits pulses and measures the phase shift between the transmitted and returned signals, which indicates the target's velocity along the radar beam.
2. The maximum unambiguous Doppler velocity (Nyquist velocity) that can be measured is determined by the radar wavelength and pulse repetition frequency. Higher velocities will appear as lower velocities (folding).
3. Distributed targets result in a spectrum of Doppler velocities being measured. The moments of the spectrum - mean velocity, spectral width, and average power - can be estimated from the autocorrelation of the signal time series without reconstructing the full spectrum.
A New Underwater Acoustic Navigation Method Based on the Doppler Principle
In this paper, a new underwater acoustic navigation method is proposed, which is named from
Doppler Acoustic Omnirange Beacon (DAOB). It is borrowed from the idea of Doppler VHF Omnirange
(DVOR) and based on the Doppler principle. The cause of Doppler effect in the received signal is the
motion or position change of one or two sources. The effect of multipath is analyzed, and an improved
signal form is presented to solve the rigorous multipath environment underwater. Some simulation is
presented to verify the performance.
Subsystems of radar and signal processing
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RADAR MEASUREMENTS LECTURE EECS BERKELY!
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asil-14
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LOW,MEDIUM,HIGH_Doppler_MTI.pdf
The document discusses MTI (Moving Target Indication) and pulse Doppler radars. It explains that MTI radars use techniques like delay line cancellation to eliminate echoes from stationary clutter and detect moving targets. Pulse Doppler radars employ the Doppler shift caused by target motion to detect targets. Key differences are noted - MTI radars have no range ambiguities but Doppler ambiguities, while pulse Doppler radars have the opposite problem. Blind speeds, limitations of CW radar, and techniques to overcome issues like flicker noise and lack of isolation are also covered. Applications of CW radar like speed measurement are mentioned.
FT NMR
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Performance analysis of wavelet based blind detection and hop time estimation...
This document discusses a wavelet-based algorithm for blind detection and hop time estimation of frequency hopping signals in the HF band.
The algorithm first uses the temporal correlation function (TCF) of the received signal to extract phase information. Discrete wavelet transform (DWT) is then applied to the TCF to detect frequency transition points, which indicate the time of hopping between frequencies. Simulation results showing the detection performance at different signal-to-noise ratios are presented.
The key steps are: 1) Extracting the phase from the TCF of the received signal. 2) Applying DWT as a de-noising technique to detect the times of hopping between frequencies. 3) Presenting simulation
Packets Wavelets and Stockwell Transform Analysis of Femoral Doppler Ultrasou...
Ultrasonic Doppler signals are widely used in the detection of cardiovascular pathologies or the evaluation of the degree of stenosis in the femoral arteries. The presence of stenosis can be indicated by disturbing the blood flow in the femoral arteries, causing spectral broadening of the Doppler signal. To analyze these types of signals and determine stenosis index, a number of time-frequency methods have been developed, such as the short-time Fourier transform, the continuous wavelets transform, the wavelet packet transform, and the S-transform
2412ijmnct02
This document summarizes the implementation of baseband acquisition and tracking modules for a GPS receiver using a digital signal processing tool. The acquisition module uses a parallel code phase search algorithm to determine the visible satellites. Initial results generating an intermediate frequency and PRN code are shown. Future work involves verifying these results and implementing the tracking module to refine code phase and frequency values to obtain navigation data. The implementation is being tested on a software-defined radio board to develop an indigenous multichannel GPS receiver.
Masters' Thesis Defense Slides
This document summarizes a research paper on detecting intruders in a wireless sensor network using low-power passive infrared (PIR) sensors. It presents an algorithm that uses the Haar transform and support vector machines to distinguish intruder signatures from clutter signatures in the sensor data. The algorithm was tested through simulations and field experiments, achieving detection rates over 90% while minimizing false alarms. However, limitations were observed when testing in high-clutter summer conditions. An analytical model of intruder signatures suggests that velocity and direction information cannot be extracted from a single sensor but may require a network of spatially distributed sensors.
IR UWB TOA Estimation Techniques and Comparison
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
FPGA Implementation of Large Area Efficient and Low Power Geortzel Algorithm ...
Spectrum analysis is very essential requirement in
instrumentation and communication signal interception
.Spectrum analysis is normally carried out by online or offline
FFT processing. But the FFT being highly mathematical
intensive, is not suitable for low area and low power
applications. Offline FFT processing can’t give the real time
spectrum estimation which is essential in communication
signal interception. Online FFT computation takes very high
resources, which makes the system costly and power hungry.
The Goertzel algorithm is a digital signal processing (DSP)
technique for identifying frequency components of a signal,
published by Dr. Gerald Goertzel in 1958. While the general
Fast Fourier transform (FFT) algorithm computes evenly
across the bandwidth of the incoming signal, the Goertzel
algorithm looks at specific, predetermined frequency. However
the implementation of Goertzel algorithm for spectrum
computation is not explored for FPGA implementation. The
FPGA being capable of offering high frequency data paths in
them become suitable for realizing high speed spectrum
analysis algorithms.
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みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
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1-Wang-FR1020-IGARSS11.pptx
- 1. Demonstration of Target Vibration Estimation in Synthetic Aperture Radar Imagery Qi Wang1,2, Matthew Pepin1,2, Ryan J. Beach2, Ralf Dunkel3, Tom Atwood2,4, Armin W. Doerry4, Balu Santhanam2, Walter Gerstle5, and Majeed M. Hayat1,2 1Center for High Technology Materials, University of New Mexico, Albuquerque, NM, 87131 USA 2Depart. of Electrical and Computer Science, University of New Mexico, Albuquerque, NM, 87131 USA 3General Atomics Aeronautics Systems, Inc., San Diego, CA 92064 USA 4Sandia National Laboratories, Albuquerque, NM 87185 USA 5Depart. of Civil Engineering, University of New Mexico, Albuquerque, NM, 87131 USA
- 2. Content Motivation Signal model Algorithm development The discrete fractional Fourier transform Experimental results Performance analysis Conclusions
- 4. The ability of remote sensing target vibrations is important:
- 5. Avoids the cost of acquiring and installing accelerometers on remote structures
- 6. Enables sensing vibrations of structures that not easily accessible
- 8. Micro-Doppler effect RF pulse: X0 y (azimuth) Frequency (Hz) t (sec) Doppler frequency caused by both the plane’s motion and target vibration Doppler frequency caused by the plane’s motion
- 11. c: speed of the microwave
- 12. V: speed of the antenna
- 13. y: azimuth position of the vibrating scatterer
- 14. fprf: the pulse repetition frequency
- 15. rd[n]: time-varying range of the vibrating scatterer
- 16. φ: other (constant) phase terms
- 17. NI: total number of pulses
- 19. Concentrates a linear chirp into a few coefficients we obtain an impulse-like transform analogous to what the discrete Fourier transform produces for a sinusoid.Intersection for α = π/2 The DFRFT of a complex-valued signal containing two component: a pure 150 Hz sinusoid and a chirp with a center frequency of 200 Hz and chirp rate of 400 Hz/s.
- 20. The DFRFT (cont’d) Let W denote the transformation matrix of the centered-DFT, the fractional power of W is defined as The DFRFT of a signal x[n] is the DFT of an intermediate signal for each index k (k = 0,1, …,N-1), that is where r = 0,1,…,N-1 is the newly introduced angular index and α=2πr/N. The intermediate signal is calculated by where vpis the pth column vector of VG. J. G. Vargas-Rubio and B. Santhanam, “On the multiangle centered discrete fractional Fourier transform,” IEEE signal Processing Letters, vol. 12, pp. 273-276, 2005
- 24. The vibration is caused by the rotation of an unbalanced mass.
- 25. Vibration magnitude: 1.5 mm; vibration frequency: 5 HzSAR image of the test ground near Julian, CA. It was generated by the Lynx system on 2010.
- 26. Experiment: the DFRFT spectra The changing of position of the peak in the DFRFT plain indicates a time-varying vibration acceleration of the target. Angle (rad) Frequency (Hz)
- 27. Estimation results Estimated vibration acceleration (x: time (s); y: acceleration ( m/s2) Estimated DFT spectrum of the vibration (x: frequency (Hz); y: magnitude (AU) Actual vibration frequency: 5 Hz
- 28. Performance analysis The vibration frequency resolution is limited by the SAR observation time of the target For the Lynx system, it ranges from 0.3 Hz to 1.0 Hz depending on the data collection geometry and the radar cross section of the target. The maximum measurable vibration frequency is upper-bounded by fprf/2 theoretically In practice, vibration frequencies up to 25 Hz can be easily estimated when fprf = 1000 Hz;
- 29. Conclusions A DFRFT-based method is proposed for SAR vibration estimation In the experiment, the proposed method successfully estimated a 1.5 mm, 5-Hz vibration from a corner reflector Performance analysis of the proposed method is carried out in terms of vibration frequency resolution and maximum measurable vibration frequency
- 30. Acknowledgement This work was supported by the United States Department of Energy (Award No. DE-FG52-08NA28782), the National Science Foundation (Award No. IIS-0813747), National Consortium for MASINT Research, and Sandia National Laboratories. The authors also thank GA-ASI for making the Lynx system available to this project.