ICASSP99 Defense and Security Applications

Defense and Security Applications
Home Full List of Titles 1: Speech Processing CELP Coding Large Vocabulary Recognition Speech Analysis and Enhancement Acoustic Modeling I ASR Systems and Applications Topics in Speech Coding Speech Analysis Low Bit Rate Speech Coding I Robust Speech Recognition in Noisy Environments Speaker Recognition Acoustic Modeling II Speech Production and Synthesis Feature Extraction Robust Speech Recognition and Adaptation Low Bit Rate Speech Coding II Speech Understanding Language Modeling I 2: Speech Processing, Audio and Electroacoustics, and Neural Networks Acoustic Modeling III Lexical Issues/Search Speech Understanding and Systems Speech Analysis and Quantization Utterance Verification/Acoustic Modeling Language Modeling II Adaptation /Normalization Speech Enhancement Topics in Speaker and Language Recognition Echo Cancellation and Noise Control Coding Auditory Modeling, Hearing Aids and Applications of Signal Processing to Audio and Acoustics Spatial Audio Music Applications Application - Pattern Recognition & Speech Processing Theory & Neural Architecture Signal Separation Application - Image & Nonlinear Signal Processing 3: Signal Processing Theory & Methods I Filter Design and Structures Detection Wavelets Adaptive Filtering: Applications and Implementation Nonlinear Signals and Systems Time/Frequency and Time/Scale Analysis Signal Modeling and Representation Filterbank and Wavelet Applications Source and Signal Separation Filterbanks Emerging Applications and Fast Algorithms Frequency and Phase Estimation Spectral Analysis and Higher Order Statistics Signal Reconstruction Adaptive Filter Analysis Transforms and Statistical Estimation Markov and Bayesian Estimation and Classification 4: Signal Processing Theory & Methods II, Design and Implementation of Signal Processing Systems, Special Sessions, and Industry Technology Tracks System Identification, Equalization, and Noise Suppression Parameter Estimation Adaptive Filters: Algorithms and Performance DSP Development Tools VLSI Building Blocks DSP Architectures DSP System Design Education Recent Advances in Sampling Theory and Applications Steganography: Information Embedding, Digital Watermarking, and Data Hiding Speech Under Stress Physics-Based Signal Processing DSP Chips, Architectures and Implementations DSP Tools and Rapid Prototyping Communication Technologies Image and Video Technologies Automotive Applications / Industrial Signal Processing Speech and Audio Technologies Defense and Security Applications Biomedical Applications Voice and Media Processing Adaptive Interference Cancellation 5: Communications, Sensor Array and Multichannel Source Coding and Compression Compression and Modulation Channel Estimation and Equalization Blind Multiuser Communications Signal Processing for Communications I CDMA and Space-Time Processing Time-Varying Channels and Self-Recovering Receivers Signal Processing for Communications II Blind CDMA and Multi-Channel Equalization Multicarrier Communications Detection, Classification, Localization, and Tracking Radar and Sonar Signal Processing Array Processing: Direction Finding Array Processing Applications I Blind Identification, Separation, and Equalization Antenna Arrays for Communications Array Processing Applications II 6: Multimedia Signal Processing, Image and Multidimensional Signal Processing, Digital Signal Processing Education Multimedia Analysis and Retrieval Audio and Video Processing for Multimedia Applications Advanced Techniques in Multimedia Video Compression and Processing Image Coding Transform Techniques Restoration and Estimation Image Analysis Object Identification and Tracking Motion Estimation Medical Imaging Image and Multidimensional Signal Processing Applications I Segmentation Image and Multidimensional Signal Processing Applications II Facial Recognition and Analysis Digital Signal Processing Education Author Index A B C D E F G H I J K L M N O P Q R S T U V W X Y Z	Audio Data Hiding By Use Of Band-Limited Random Sequences Authors: Mikio Ikeda, Kazuya Takeda, Fumitada Itakura, Page (NA) Paper number 1820 Abstract: This paper proposes the use of band-limited random sequences to introduce further flexibility in the spread spectrum based audio data hiding. To realize the sub-band data hiding, a systematic method is developed in order to generate band-limited and orthonormal random sequences of any length. In experiments, we evaluated the selective use of frequency channels to be used for information embedding, and the robustness against the MPEG1 layer 3 encoding and decoding. From the results, it is clarified that the proposed method is robust against more than 160 kbps MPEG1 coding and decoding when the center frequency of the sub-band is lower than 11 kHz. IC991820.PDF (From Author) IC991820.PDF (Rasterized) TOP Image Domain Feature Extraction from Synthetic Aperture Imagery Authors: Michael A Koets, Randolph L Moses, Page (NA) Paper number 2438 Abstract: We consider the problem of estimating a parametric model that describes radar backscattering from synthetic aperture radar imagery. We adopt a scattering center model that incorporates both frequency and aspect dependence of scattering. We develop an approximate maximum likelihood algorithm for parameter estimation directly on regions of the SAR image. The algorithm autonomously selects model order and structure. Results are presented for both synthetic and measured SAR imagery, and algorithm accuracy is compared with the Cramer-Rao bound. IC992438.PDF (From Author) IC992438.PDF (Rasterized) TOP Clutter Mitigation Techniques for Space-Based Radar Authors: Stephen M Kogon, Daniel J Rabideau, Richard M Barnes, Page (NA) Paper number 2116 Abstract: The mission of a ground moving target indication (GMTI) radar, as its name implies, is to detect and classify ground-based vehicles, even ones with very low velocities. This type of radar can provide a wide area of coverage and frequent updates of a specific area of interest if the radar is placed in a low earth orbit. However, because of the large footprint of the radar on the ground and the high satellite velocity, target signals must compete with very strong, nearby clutter. This paper describes how space-time adaptive processing (STAP) can be used for the purposes of clutter rejection in order to perform the GMTI function. In addition, we confront several important issues for a space-based radar such as pulse repetition frequency (PRF) selection, the choice of a STAP algorithm, and the number of spatial channels. These results are quantified in terms of clutter cancellation and angle accuracy. IC992116.PDF (From Author) IC992116.PDF (Rasterized) TOP Classification Of Landmine-Like Metal Targets Using Wideband Electromagnetic Induction Authors: Ping Gao, Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708-0291 (U.K.) Leslie M Collins, Department of Electrical and Computer Engineering, Duke University, Durham NC 27708-0291 (U.K.) Norbert Geng, Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708-0291 (U.K.) Lawrence Carin, Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708-0291 (U.K.) Dean A Keiswetter, I. J Won, Page (NA) Paper number 1783 Abstract: Our previous work has indicated that the careful application of signal detection theory can dramatically improve detectability of landmines using time-domain electromagnetic induction (EMI) data [L. Collins, P. Gao, and L. Carin, IEEE Trans. Geosc. Remote Sens., in press]. In this paper, classification of various metal targets via signal detection theory is investigated using a prototype wideband frequency-domain EMI sensor [I.J. Won, D.A. Keiswetter, and D.R. Hansen, J. Envir. Engin. Geophysics, 2:53-64 (1997)]. An algorithm that incorporates both the uncertainties regarding the target-sensor orientation and a theoretical model of the response of such a sensor is developed. The performance of this approach is evaluated using both simulated and experimental data. The results show that this approach affords substantial classification performance gains over the traditional matched filter approach, on the average by 60%. IC991783.PDF (Scanned) TOP