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IEEE Transactions on Signal Processing. 01/2011; 59:3434-3440.
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Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010, 14-19 March 2010, Sheraton Dallas Hotel, Dallas, Texas, USA; 01/2010
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IEEE Transactions on Signal Processing. 01/2010; 58:67-83.
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IEEE Transactions on Signal Processing. 01/2009; 57:4522-4537.
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Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009, 19-24 April 2009, Taipei, Taiwan; 01/2009
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IEEE Transactions on Signal Processing. 01/2009; 57:4598-4615.
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ABSTRACT: This paper investigates the Doppler-bearing tracking problem in the presence of random observer position error at one or two active observers. We first derive the CRLBs for the target and observer location parameters when the noise is Gaussian. The CRLB results indicate that the observer position uncertainty always leads to degradation in the target location estimation accuracy in both the two-observer and single-observer tracking scenarios. In the two-observer case, the Doppler-bearing measurements may be able to improve the observer positions while in the single-observer case, they cannot. This paper then studies the MSE of the target parameter estimate when the observer positions are assumed accurate but in fact have error. We show that for the two-observer case, the MSE is larger than the CRLB of the target parameter vector and thus, it is necessary for an algorithm to take the observer position error into account to achieve the optimum performance. On the other hand, for the single-observer case, the MSE is identical to the CRLB, indicating that the identification of the observer position can be eliminated without sacrificing the estimation accuracy of the target position. Simulations confirm the theoretical results.
IEEE Transactions on Signal Processing 09/2008; · 2.63 Impact Factor
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ABSTRACT: This paper investigates the use of energy measurements to improve the localization accuracy in terms of range and bearing in a TDOA based system. We first extend the hybrid energy and TDOA localization algorithm in Cartesian coordinate that is proposed in (Ho and Sun, 2008) to obtain the range and bearing estimates of an emitting source. The accuracy of the range and bearing estimates is then examined with respect to the noise level in the energy measurements relative to that in TDOAs. For comparison purpose, the CRLB for the range and bearing estimates is also derived. We find that energy measurements improve more the accuracy in range than in bearing. Regarding the bearing estimation, the energy measurements provide more improvement for a near-field source than for a far-field source.
Sensor Array and Multichannel Signal Processing Workshop, 2008. SAM 2008. 5th IEEE; 08/2008
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ABSTRACT: The partial adaptive concentric ring array (CRA) has been successfully applied to 3D beamforming because of its flexibility, faster tracking ability and reduced computation with respect to the fully adaptive CRA. In some cases, prior knowledge regarding some interferences is available so that better beamformers can be designed. The previous method that exploits prior knowledge by using a fixed penalty factor could not guarantee in maintaining a low residual interference and noise level. We propose in this paper an adaptive beamformer that automatically seeks out the optimum penalty factor to achieve the best performance. The proposed beamformer outperforms the previous design in maintaining a higher output signal to interference and noise ratio, even after the characteristics of the interferences have changed. The performance of the proposed beamformer is evaluated through simulations.
Sensor Array and Multichannel Signal Processing Workshop, 2008. SAM 2008. 5th IEEE; 08/2008
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ABSTRACT: Ground penetrating radar (GPR)-based discrimination of landmines from clutter is known to be challenging due to the wide variability of possible clutter (e.g., rocks, roots, and general soil heterogeneity). This paper discusses the use of GPR frequency-domain spectral features to improve the detection of weak-scattering plastic mines and to reduce the number of false alarms resulting from clutter. The motivation for this approach comes from the fact that landmine targets and clutter objects often have different shapes and/or composition, yielding different energy density spectrum (EDS) that may be exploited for their discrimination (this information is also present in time-domain data, but in the frequency domain we can remove a phase if desired and can reveal better spatial characteristics and therefore often achieve greater robustness). This paper first applies the finite-difference time-domain (FDTD) modeling technique to establish the theoretical foundation. The method to generate EDS from GPR measurements is then described. The consistency of the frequency-domain features is examined through two different GPRs that have different spatial sampling rates and frequency bandwidths. Experimental results from several test sites, based on GPR data collected over buried mines and emplaced buried clutter objects, corroborate the theoretical development and the effectiveness of the proposed spectral feature to increase the accuracy of landmine detection and discrimination.
IEEE Transactions on Geoscience and Remote Sensing 05/2008; · 2.89 Impact Factor
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ABSTRACT: This paper proposes a technique for using infrared (IR) imagery to eliminate false forward-looking ground penetrating radar (FLGPR) detections by examining areas in IR images corresponding to FLGPR alarm locations. The FLGPR and IR co-location is based on the assumption of a flat earth and the pinhole camera model. The parameters of the camera and its location on the vehicle are not assumed to be known. The parameters of the model are estimated using a set of correspondences gathered from the data utilizing the covariance matrix adaptation evolution strategy (CMA-ES) optimization algorithm. Detection of false alarms is accomplished by generating a descriptor, consisting of various statistics calculated from the IR images along with the FLGPR confidence value, for each alarm location. The alarms are then classified based on the Mahalanobis distance between their descriptor and a multivariate normal distribution used to model false alarms. The false alarm distribution is computed from training data where the validity of each alarm location is already known. Using this technique, generally fifteen to twenty percent or more of the FLGPR false alarms can be eliminated without losing any true alarms.© (2008) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
04/2008;
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ABSTRACT: A source signal will be subject to different amounts of time-delay as well as attenuation when it reaches a number of spatially separated sensors. Both time-delay and attenuation are dependent on the distance between the source and the receivers. This paper performs a fundamental investigation of whether the gain ratios of arrival (GROAs), defined here as the ratio of the received signal amplitudes at the referenced sensor to the other sensors, can be utilized in conjunction with the time differences of arrival (TDOAs) to improve the source localization accuracy. We begin with a Gaussian random signal model and derive the Cramer-Rao lower bound (CRLB) of a source location estimate based on both GROAs and TDOAs. Our conclusion is that the improvement from GROAs increases when the factor c/omega<sub>o</sub> increases, where c is the signal propagation speed and omega<sub>o</sub> is the signal bandwidth. The paper proceeds to develop an algebraic closed-form solution for the source location using GROAs and TDOAs. The algebraic solution is proved theoretically to reach the CRLB accuracy under the Gaussian data model. Numerical simulations are included to support and corroborate the theoretical developments.
IEEE Transactions on Signal Processing 03/2008; · 2.63 Impact Factor
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ABSTRACT: Prefilters are generally applied to the discrete multiwavelet transform (DMWT) for processing scalar signals. To fully utilize the benefit offered by DMWT, it is important to have the prefilter designed appropriately so as to preserve the important properties of multiwavelets. To this end, we have recently shown that it is possible to have the prefilter designed to be maximally decimated, yet preserve the linear phase and orthogonal properties as well as the approximation power of multiwavelets. However, such design requires the point of symmetry of each channel of the prefilter to match with the scaling functions of the target multiwavelet system. It can be very difficult to find a compatible filter bank structure; and in some cases, such filter structure simply does not exist, e.g., for multiwavelets of multiplicity 2. In this paper, we suggest a new DMWT structure in which the prefilter is combined with the first stage of DMWT. The advantage of the new structure is twofold. First, since the prefiltering stage is embedded into DMWT, the computational complexity can be greatly reduced. Experimental results show that an over 20% saving in arithmetic operations can be achieved comparing with the traditional DMWT realizations. Second, the new structure provides additional design freedom that allows the resulting prefilters to be maximally decimated, orthogonal and symmetric even for multiwavelets of low multiplicity. We evaluated the new DMWT structure in terms of computational complexity, energy compaction ratio as well as the compression performance when applying to a VQ based image coding system. Satisfactory results are obtained in all cases comparing with the traditional approaches.
IEEE Transactions on Signal Processing 01/2008; · 2.63 Impact Factor
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Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2008, March 30 - April 4, 2008, Caesars Palace, Las Vegas, Nevada, USA; 01/2008
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IEEE Transactions on Signal Processing. 01/2008; 56:5758-5772.
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IEEE Transactions on Signal Processing. 01/2008; 56:464-477.
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ABSTRACT: The localization of an acoustic source can be based on the energy measurements at a number of spatially separated microphones. This is because the amount of source energy attenuation at a microphone is proportional to the square of the distance between the source and the microphone. This paper develops an algebraic closed-form solution for the acoustic source localization problem using energy measurements, under the condition of direct line-of-sight and free space propagation. First-order analysis is applied to the proposed solution to study its performance, where only the linear noise terms are kept in obtaining the mean-square localization error. The first-order analytical results show that the proposed solution reaches the Cramer-Rao lower bound (CRLB) accuracy for Gaussian noise as the signal-to-noise ratio tends to infinity. In addition, the proposed solution provides much better accuracy than other closed-form solutions available in literature. Improvement on the proposed solution that extends its operating range beyond the threshold noise level was made by imposing nonnegative constraints. Simulations are included to corroborate the performance of the proposed method.
IEEE Transactions on Audio Speech and Language Processing 12/2007; · 1.50 Impact Factor
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ABSTRACT: A variety of algorithms for the detection of landmines and discrimination between landmines and clutter objects have been presented. We discuss four quite different approaches in using data collected by a vehicle-mounted ground-penetrating radar sensor to detect landmines and distinguish them from clutter objects. One uses edge features in a hidden Markov model; the second uses geometric features in a feed-forward order-weighted average network; the third employs spectral features as its basis; and the fourth clusters edge histograms. We present the results of a large-scale cross-validation evaluation that uses a diverse set of data collected over 41 807.57 m<sup>2</sup> of ground, including 1593 mine encounters. Finally, we discuss the results of that ranking and what one can conclude concerning the performance of these four algorithms in various settings.
IEEE Transactions on Geoscience and Remote Sensing 09/2007; · 2.89 Impact Factor
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ABSTRACT: The generalized sidelobe canceller (GSC) efficiently realizes the optimal linearly constrained minimum variance (LCMV) beamformer and delivers excellent beamforming results by reducing directional interference and noise. However, when the input signals are contaminated by other type of noises, such as background and diffused noises, the overall performance of GSC can be even worse than the traditional delay-and-sum beamformers. In this paper, we investigate the application of the spatially adaptive multiwavelet (MWT) denoising technique to the GSC in an environment with severe diffused noise. Comparing with the traditional scalar wavelets, the multiwavelets can better characterize the noise information in the signal such that better denoising performance can be achieved. Different approaches for integrating the GSC and the multiwavelet denoiser were studied. It is found that by adding two denoisers, one to the fixed constrained part and another to the final GSC output, an improvement of 2dB in SNR can be achieved as compared with the traditional GSC method
Circuits and Systems, 2007. ISCAS 2007. IEEE International Symposium on; 06/2007
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ABSTRACT: When overlaying spread spectrum (SS) transmission over a narrowband system, the performance of the spread spectrum system will be significantly degraded due to the interference from the narrowband signal. This paper proposes two computationally attractive and efficient adaptive techniques for narrowband interference (NBI) suppression in DS-CDMA system: adaptive linear predictor algorithm and adaptive NBI re-estimation algorithm. Unlike existing techniques in literature which use either estimator/subtracter approach or code-aided approach, the proposed methods combine these two approaches together and show that a much better performance can be achieved. In addition, the proposed algorithms are blind and do not require any training symbols and interference characteristics. The proposed methods not only provide faster convergence speed than the pure code-aided approach (without using a predictor and subtractor), but also give better BER performance
IEEE Transactions on Wireless Communications 04/2007; · 2.59 Impact Factor
