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19
Adaptive TimeVarying Cancellation of Wideband Interferences in SpreadSpectrum Communications Based on TimeFrequency Distributions
 IEEE Trans. Signal Processing
, 1999
"... The aim of this paper is to propose an adaptive method for suppressing wideband interferences in spread spectrum (SS) communications. The proposed method is based on the timefrequency representation of the received signal from which the parameters of an adaptive timevarying interference excision ..."
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The aim of this paper is to propose an adaptive method for suppressing wideband interferences in spread spectrum (SS) communications. The proposed method is based on the timefrequency representation of the received signal from which the parameters of an adaptive timevarying interference excision filter are estimated. The approach is based on the generalized WignerHough transform as an effective way to estimate the instantaneous frequency of parametric signals embedded in noise. The performance of the proposed approach is evaluated in the presence of linear and sinusoidal FM interferences plus white Gaussian noise in terms of SNR improvement factor and bit error rate (BER).
Array processing for nonstationary interference suppression in DS/SS communications using subspace projection techniques
"... Combined spatial and timefrequency signatures of signal arrivals at a multisensor array are used for nonstationary interference suppression in directsequence spreadspectrum (DS/SS) communications. With random PN spreading code and deterministic nonstationary interferers, the use of antenna array ..."
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Cited by 11 (6 self)
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Combined spatial and timefrequency signatures of signal arrivals at a multisensor array are used for nonstationary interference suppression in directsequence spreadspectrum (DS/SS) communications. With random PN spreading code and deterministic nonstationary interferers, the use of antenna arrays offers increased DS/SS signal dimensionality relative to the interferers. Interference mitigation through spatiotemporal subspace projection technique leads to reduced DS/SS signal distortion and improved performance over the case of a single antenna receiver. The angular separation between the interference and desired signals is shown to play a fundamental role in trading off the contribution of the spatial and timefrequency signatures to the interference mitigation process. The expressions of the receiver SINR implementing subspace projections are derived and numerical results are provided.
Subspace Array Processing for the Suppression of FM Jammers in GPS Receivers
"... This paper applies the subspace projection array processing techniques for suppression of frequency modulated (FM) jammers in GPS receivers. The FM jammers are instantaneous narrowband and have clear timefrequency (tf) signatures that are distinct from the GPS C/A spread spectrum code. In the prop ..."
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Cited by 11 (6 self)
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This paper applies the subspace projection array processing techniques for suppression of frequency modulated (FM) jammers in GPS receivers. The FM jammers are instantaneous narrowband and have clear timefrequency (tf) signatures that are distinct from the GPS C/A spread spectrum code. In the proposed technique, the instantaneous frequency (IF) of the jammer is estimated and used to construct the jammer subspace. With a multisensor receiver, both spatial and timefrequency signatures of signal arrivals are used for effective interference suppression. This paper considers the deterministic nature of the GPS C/A code. We derive the receiver SINR, which shows improved performance in strong interference environments. 1.
Separating More Sources Than Sensors Using TimeFrequency Distributions
 IN PROC. ISSPA, VOL. II
, 2004
"... This paper deals with the problem of blind separation of nonstationary sources in the underdetermined case, i.e. more sources than sensors, using timefrequency distributions (TFDs). We propose a new algorithm to achieve the separation based on a main assumption of timefrequency (TF) disjoint sou ..."
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Cited by 10 (1 self)
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This paper deals with the problem of blind separation of nonstationary sources in the underdetermined case, i.e. more sources than sensors, using timefrequency distributions (TFDs). We propose a new algorithm to achieve the separation based on a main assumption of timefrequency (TF) disjoint sources that allows an explicit exploitation of nonstationarity. The algorithm proceeds through four main procedures: (i) computation of the spatial timefrequency distribution (STFD) matrices of the mixed observations, and noise thresholding; (ii) a testing procedure is then applied to separate the autosource TF points from crosssource TF points by applying an appropriate testing criterion; (iii) vector clustering to obtain the TF signatures of sources, hence their TFDs; and (iv) recovery of original source waveforms from their estimate TFDs using TF synthesis. Simulated experiments indicated the success of the proposed algorithm in different scenarios. Moreover, we propose two other modified versions of the algorithm to better deal with autosource TF point selection.
Empirical Mode Decomposition and Blind Source Separation Methods for Antijamming with GPS Signals
"... Abstract The spreadspectrum structure of GPS signals provides inherent jamming tolerance for GPS receivers. In a hostile environment where jamming sites may be close to GPS users, a larger JSR is possible. How to achieve the desired accuracy for GPSbased systems in the presence of strong jamming ..."
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Abstract The spreadspectrum structure of GPS signals provides inherent jamming tolerance for GPS receivers. In a hostile environment where jamming sites may be close to GPS users, a larger JSR is possible. How to achieve the desired accuracy for GPSbased systems in the presence of strong jamming is an important but outstanding problem. Here we propose to use the empiricalmode decomposition (EMD) method, originally developed for analyzing nonlinear and nonstationary signals, for antijamming. Given a jammed, noisy GPS signal, the EMD method identifies the innate undulations belonging to different time scales and sifts them out to yield a small number of intrinsic modes. We find that the EMD method typically works well when the jamming is stationary in that the GPS signal and jamming components are typically contained in different intrinsic modes. However, when the jamming is nonstationary, the GPS signal and jamming are spread over all the intrinsic modes. Our solution is to use the blindsource separation (BSS) method operating on the set of intrinsic modes from EMD. Simulations indicated that this combined EMD/BSS methodology works reasonably well for extracting the GPS signal in the presence of nonstationary jamming for JSR up 45dB.
Implementation of Instantaneous Frequency Estimation based on TimeVarying AR Modeling
, 2009
"... Instantaneous Frequency (IF) estimation based on timevarying autoregressive (TVAR) modeling has been shown to perform well in practical scenarios when the IF variation is rapid and/or nonlinear and only short data records are available for modeling. A challenging aspect of implementing IF estimati ..."
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Instantaneous Frequency (IF) estimation based on timevarying autoregressive (TVAR) modeling has been shown to perform well in practical scenarios when the IF variation is rapid and/or nonlinear and only short data records are available for modeling. A challenging aspect of implementing IF estimation based on TVAR modeling is the efficient computation of the timevarying coefficients by solving a set of linear equations referred to as the generalized covariance equations. Conventional approaches such as Gaussian elimination or direct matrix inversion are computationally inefficient for solving such a system of equations especially when the covariance matrix has a high order. We implement two recursive algorithms for efficiently inverting the covariance matrix. First, we implement the Akaike algorithm which exploits the blockToeplitz structure of the covariance matrix for its recursive inversion. In the second approach, we implement the WaxKailath algorithm that achieves a factor of 2 reduction over the Akaike algorithm in the number of recursions involved and the computational effort required to form the inverse matrix. Although a TVAR model works well for IF estimation of frequency modulated (FM)
Society of PhotoOptical Instrumentation Engineers
"... University. His general research interests lie in the areas of statistical signal and array processing with applications to communications, radar, navigation, radio frequency identification (RFID), and ultrasonic nondestructive evaluations. He is a Senior Member of the Institute of Electrical and El ..."
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University. His general research interests lie in the areas of statistical signal and array processing with applications to communications, radar, navigation, radio frequency identification (RFID), and ultrasonic nondestructive evaluations. He is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) and the
A WAVELET PACKET TRANSFORMBASED APPROACH FOR INTERFERENCE MEASUREMENT IN SPREAD SPECTRUM WIRELESS COMMUNICATION SYSTEMS
, 2003
"... Abstract − The paper mainly concerns interference measurement in spread spectrum, wireless communication systems. A new digital signalprocessing method is proposed, which proves non intrusive and independent of the specific system considered. Thanks to the nice properties of the wavelet packet tran ..."
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Abstract − The paper mainly concerns interference measurement in spread spectrum, wireless communication systems. A new digital signalprocessing method is proposed, which proves non intrusive and independent of the specific system considered. Thanks to the nice properties of the wavelet packet transform, the method is capable of extracting the occurred interference from the spread spectrum signal, thus ensuring accurate interference magnitude and frequency estimates also in critical conditions: interference level much smaller than that characterizing the spread spectrum signal, and interference spectral content very close to the carrier centre frequency of the considered system.
Biography
"... Software Radio (SDR) based Global Navigation Satellite Systems (GNSS) receiver frontend design, jitter analysis of GNSS signals, Analog to Digital Convertors (ADCs) and sampling techniques for multiple GNSS signals. This paper analyzes the effects of jitter on the GPS and Galileo navigation signals ..."
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Software Radio (SDR) based Global Navigation Satellite Systems (GNSS) receiver frontend design, jitter analysis of GNSS signals, Analog to Digital Convertors (ADCs) and sampling techniques for multiple GNSS signals. This paper analyzes the effects of jitter on the GPS and Galileo navigation signals. Jitter effects have usually been modelled as additive noise, based on a sinusoidal input signal, and limits the achievable SignaltoNoise Ratio (SNR). Analysis shows that pseclevel jitter specifications are required in order to keep jitter noise well below the thermal noise for software radio satellite navigation receivers. However, analysis of a BPSK system shows that large errors occur if the jittered sample crosses a data bit boundary. Quadrature Phase Shift Keying (QPSK) modulation achieves greater bandwidth efficiency than BPSK. The new GPS L5 signal is QPSK modulated. The Binary Offset Carrier (BOC) spreading modulation has recently been recommended by GPSGalileo Working group on Interoperability and Compatibility for adoption by Europe’s Galileo program for its Open Service (OS) signal at the L1 frequency and by the United Sates for its modernized GPS L1 Civil (L1C) signal. BOC signals have more transitions and hence jitter creates more woes. The aim of this paper is to derive expressions for noise due to jitter taking into account the transitions probability in QPSK and BOC systems. Both simulations and analysis are used to give a better understanding of jitter effects on Software Radio GNSS receivers. 1
NarrowBand Interference Suppression In Direct Sequence Spread
 in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing (ICASSP
, 1997
"... This paper proposes an algorithm for the suppression of narrowband interference in direct sequence spread spectrum (DSSS) systems, based on the open loop adaptive IIR notch filtering. The center frequency of the interference is monitored online by the adaptive lattice IIR notch filter in [6] or by ..."
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This paper proposes an algorithm for the suppression of narrowband interference in direct sequence spread spectrum (DSSS) systems, based on the open loop adaptive IIR notch filtering. The center frequency of the interference is monitored online by the adaptive lattice IIR notch filter in [6] or by timefrequency analysis in [3]. The power of the interference signal is also estimated from the adaptive filters. Another lattice IIR notch filter is placed in front of the receiver, the notch of which is controlled by the frequency estimate to remove the interference. However, the IIR notch filter with the zeros on the unit circle also removes the information signal at the notch frequency while removing the interference and causes data distortion. Hence, the depth of the notch should also be adjusted for the tradeoff between data distortion and effective interference reduction. The objective function for adjusting the depth of the notch is defined as the overall signal to noise ratio (SNR). The SNR is expressed as a function of filter parameters and the notch depth that maximizes the SNR is found. Simulation results show that the proposed algorithm yields better performance than the existing FIR notch filter [3] and the conventional FIR LMS algorithm with very long taps [1].