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Abstract - SSAP4

SSAP4.1	Eigenstructure Beamspace Root Estimator Bank with Interpolated Array A. Gershman, J. Bohme (Ruhr University of Bochum, Germany) A beamspace root modification of PseudoRandom Joint Estimation Strategy (PR-JES) [1] is developed. The essence of PR-JES is to generate the eigenstructure-based estimator bank for given sample covariance or data matrix. Combining the results of ``parallel'' underlying estimators, PR-JES removes the outliers and improves the threshold performance. In the case of non-uniform array, the interpolated array approach is used to enable the application of root underlying estimators. Simulations and results of real ultrasonic data processing show that the proposed beamspace root implementation significantly outperforms spectral elementspace PR-JES and achieves the performance similar or better than that of stochastic ML method.
SSAP4.2	Minimum-Noise-Variance Beamformer with an Electromagnetic Vector Sensor A. Nehorai (The University of Illinois, Chicago, USA); K. Ho (Centre for Signal Processing, Singapore); B. Tan (National University of Singapore, Singapore) We develop a minimum-noise-variance beamformer employing one electromagnetic vector sensor, capable of measuring the complete electric and magnetic fields induced by electromagnetic signals at one point. Two types of signals are considered: one carries a single message, and the other carries two independent messages simultaneously. The state of polarization of the interference under consideration ranges from completely polarized to unpolarized. To analyze the performance, we first obtain explicit expressions for the signal to interference-plus-noise ratio (SINR) in terms of the parameters of the desired signal, interference and noise. Then we discuss some physical implications associated with the SINR expressions. Our SINR expressions provide a basis for effective interference suppression, as well as generation of dual-message signals of which the two message signals have minimum interference effect on one another.
SSAP4.3	Performance of OTH Radar Array Calibration I. Solomon (Defence Science and Technology Organisation, Australia); Y. Abramovich, D. Gray (CRC for Sensor Signal & Info. Process., Australia); S. Anderson (Defence Science and Technology Organisation, Australia) Array calibration algorithms for over-the-horizon (OTH) radar arrays have been recently proposed in the literature. These algorithms perform array calibration by using echoes from ionized meteor trails, and estimate sensor position errors and mutual coupling. In this paper we derive the Cramer-Rao performance bound for this array calibration problem and then investigate the performance bound. We obtain insight on the achievable accuracy as a function of the signal-to-noise ratio, number of snapshots and number of sources. Further, we consider the advantage of using sources with known bearings, as opposed to unknown bearings, and consider the identifiability of the array calibration problem.
SSAP4.4	Broadband Frequency Invariant Beamforming Method with Low Computational Cost T. Taniguchi (Japan) This paper presents a method for reducing the computational complexity required for farfield broadband beamforming. First, the propagating wave received by a linear or planar array of sensors is sampled efficiently on the multidimensional frequency plane in spatio-temporal sense so that the so-called non-physical area where no spectrum exists is filled with aliasing component. Next, the derived time-space series is upsampled and processed by a multidimensional filter to derive the target beampattern. Through some considerations and examples, it is shown that this method has some restrictions on the beamwidth and/or maximum beam center angle, but it can reduce the operations to about half the number of conventional one.
SSAP4.5	An Optimum Space-Time MTI Processor for Airborne Radar H. Sung (Yonsei University, Korea); Y. Park (Samsung Biom. Res. Inst., Korea); D. Youn (Yonsei University, Korea); V. Mathews (University of Utah, USA) This paper presents an optimum space-time moving target indication (MTI) processor for the airborne radar. The optimization is based on a stochastic target model, rather than deterministic target models adopted in most space-time MTI processor designs. The optimum solution that maximizes the improvement factor yielded by the processor is shown to be the generalized eigenvector corresponding to the smallest generalized eigenvalue of the signal and clutter covariance matrices. A suboptimal, but computationally simpler solution to this problem is also derived. This approach requires the solution of a linearly constrained minimum variance (LCMV) problem. Unlike typical LCMV problems, our solution also calculates the response vector specifying the frequency response along the look direction. Experimental results demonstrating the usefulness of our methods are included in the paper. The results indicate that the suboptimal solution does not suffer from significant performance loss.
SSAP4.6	An Adaptive Monopulse Processor for Angle Estimation in a Mainbeam Jamming and Coherent Interference Scenario Y. Seliktar (Georgia Institute of Technology, USA); E. Holder (Georgia Tech Research Institute, USA); D. Williams (Georgia Institute of Technology, USA) Mainbeam jamming poses a particularly difficult challenge for conventional monopulse radars. In such cases spatially adaptive processing provides some interference suppression when the target and jammer are not exactly co-aligned, but the resulting array pattern is too distorted to be suitable for monopulse processing. The presence of coherent multipath in the form of terrain scattered interference (TSI) is normally considered a nuisance source of interference. However, it can also be exploited to suppress mainbeam jamming with space-time processing. Here we present a method for incorporating space-time processing into monopulse processing to yield a space-time monopulse processor with distortionless spatial array patterns that can achieve far better mainbeam jamming cancelation and target angle estimation than has been previously possible. Performance results for the monopulse processor are obtained for Mountaintop data containing a jammer and TSI, that demonstrate a dramatic improvement in performance over conventional monopulse and spatially adaptive monopulse.
SSAP4.7	Broadband Beamforming Using Elementary Shape Invariant Beampatterns T. Abhayapala, R. Kennedy, R. Williamson (Australian National University, Australia) This paper presents a new method of designing a beamformer having a desired beampattern with focusing capability to operate at any radial distance from the array origin. An important consequence of our result is that the beamformer can be factored in to three levels of filtering: (i) beampattern independent elementary beamformers; (ii) beampattern shape dependent filters; and (iii) radial zooming filters where a single parameter can be adjusted to zoom-focus the array to a desired radial distance from the array origin. As an illustration the method is applied to the problem of producing a practical array design that achieves a frequency invariant beampattern over the frequency range of 1:10.
SSAP4.8	Near Field Superdirectivity (NFSD) W. Tager (CNET France Telecom, France) In some array applications, the source of interest is close to the array, so that we have to use a near field model. Almost always the near field is considered as an additional difficulty. We contradict this point of view and show that if the desired source is in the near field and the other sources are in the far field, then even a small array can be at the same time highly directive and comparatively robust. Instead of relying on small phase differences for low frequencies, we fully exploit the fact that the amplitude vector of the source of interest is different from that of any other source. The array geometry should be chosen to enhance this effect. Unlike far field superdirectivity, we can steer the main lobe to arbitrary directions without prohibitive loss of performance. We applied our method to microphone array sound pick up for workstations. Simulation results and measurements of a real time implementation on a fixed point DSP are provided.
SSAP4.9	Harmonic Phase Coupling for Battlefield Acoustic Target Identification D. Lake (Army Research Lab, USA) Target identification using battlefield acoustic sensor arrays is an important problem for the Army. Acoustic signatures of targets of interest, such as tanks and trucks, exhibit time-varying patterns of harmonic amplitudes that facilitate target ID. In this paper, harmonic phase coupling is shown to also be present in these acoustic signatures though issues remain to fully exploit these relationships for target ID. With all else being equal, frequencies with simple harmonic relationships, such as 2 to 1 or 3 to 2, are preferred to produce stable features. Also, naive use of FFT approaches to estimate phase leads to erratic estimates. Cramer-Rao bounds (CRB) are presented and provide insights into the limitations of the accuracy of phase coupling estimates and suggests the value of developing nonstationary methods.
SSAP4.10	DOA Estimation with Hexagonal Arrays Z. Tian, H. Van Trees (George Mason University, USA) Hexagonal arrays are widely used in practice but have received less attention in the optimum array processing literature. In this paper, we show how unitary ESPRIT can be applied to hexagonal arrays for direction-of-arrival (DOA) estimation. The resulting estimates exhibit good threshold behavior, and are close to the Cramer-Rao bound above threshold. We also show how to use spatial smoothing in hexagonal arrays for DOA estimation in the presence of coherent signals.

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