Arnab Shaw | Wright State University (original) (raw)

Papers by Arnab Shaw

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016

A novel method for signal subspace processing in the beamspace of a true time delay (TTD) beamfor... more A novel method for signal subspace processing in the beamspace of a true time delay (TTD) beamformer bank is presented. The method permits the directions of arrival of broadband sources to be estimated accurately, efficiently and non-iteratively. This is achieved by exploiting the properties of the TTD beamformer bank, which simultaneously introduces spatial diversity into the data set while maintaining the broadband nature of the data. The beamspace manifold is derived and simulation results are presented. The method is shown to improve on the processing efficiency of previous broadband methods while maintaining source location estimation accuracy superior to conventional methods. It is also shown to resolve closely spaced and disparately spaced sources in a single algorithmic pass. The method is compared to previous method in terms of bias and RMSE.

2010 IEEE International Symposium on Phased Array Systems and Technology, 2010

Abstract Radio Frequency (RF) source location methods for wide bandwidth sources are well known. ... more Abstract Radio Frequency (RF) source location methods for wide bandwidth sources are well known. Such methods typically assume that a wide bandwidth array is available in order to collect the signal data. A number of techniques have been derived from the coherent signal subspace method, but often suffer from limitations such as the requirement for preliminary source location estimates, iteration of the technique, computational expense or others. The common theme among many of these is to divide the collected data into a ...

2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2012

Abstract The authors examine a technique to apply coherent signal subspace processing in the beam... more Abstract The authors examine a technique to apply coherent signal subspace processing in the beam-space of a bank of true time delay beamformers. The technique is shown to be capable of resolving closely spaced sources while being inherently wideband in nature, computationally less expensive than many previous wideband coherent integration techniques, and does not rely on a preliminary angle of arrival estimate. The technique is examined for performance with various levels of noise in the system compared to previous ...

2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2012

Abstract The authors examine optimization of the antenna array beamformer bank for a technique to... more Abstract The authors examine optimization of the antenna array beamformer bank for a technique to apply coherent signal subspace processing in the beam-space of a bank of true time delay beamformers. This technique offers computational expense advantages over element-space methods, Mean Square Error (MSE) performance similar to wideband coherent subspace techniques and is frequency invariant. This article reports on simulation experiments to improve the true time delay beamformer bank configuration so as to ...

A time-delay neural network (TDNN) architecture is used for speaker independent recognition of th... more A time-delay neural network (TDNN) architecture is used for speaker independent recognition of the long vowel sounds. A brief introduction to the TDNN architecture and a description of the data used for the simulation are given. Previously published work is extended by training the network with the linear predictive coding (LPC) coefficients of speech along with fast Fourier transform bin energies and by allowing longer and variable length utterances. The training has been performed with multiple speakers using English ...

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016

Test of orthogonality of projected subspaces (TOPS) estimates directions of arrival of wideband s... more Test of orthogonality of projected subspaces (TOPS) estimates directions of arrival of wideband sources by exploiting orthogonality between signal and noise subspaces in spectral domain. TOPS performs well at mid signal-to-noise ratio (SNR) range, but fares poorly at high SNR and noise-free cases. The TOPS pseudospectrum often exhibits spurious peaks at all SNR levels. This paper attempts to explain the cause of poor performance, and proposes suitable modifications to extend the effectiveness of TOPS from low SNR to noise-free case. The proposed modified-TOPS (mTOPS) achieves reduction in spurious peaks by incorporating signal-subspace projection instead of null-space projection used in TOPS. It also uses trace as performance metric, instead of loss of rank used in TOPS. The effectiveness of mTOPS has been studied via simulations.

Index Terms—Array signal processing, direction of arrival (DOA) estimation, DOA, high resolution, test of orthogonality of projected subspaces (TOPS), wideband sources.

Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VI, 2015

In vehicle target classification, contact sensors have frequently been used to collect data to si... more In vehicle target classification, contact sensors have frequently been used to collect data to simulate laser vibrometry data. Accelerometer data has been used in numerous literature to test and train classifiers instead of laser vibrometry data [1] . Understanding the key similarities and differences between accelerometer and laser vibrometry data is essential to keep progressing aided vehicle recognition systems. This paper investigates the contrast of accelerometer and laser vibrometer data on classification performance. Research was performed using the end-to-end process previously published by the authors to understand the effects of different types of data on the classification results. The end-to-end process includes preprocessing the data, extracting features from various signal processing literature, using feature selection to determine the most relevant features used in the process, and finally classifying and identifying the vehicles. Three data sets were analyzed, including one collection on military vehicles and two recent collections on civilian vehicles. Experiments demonstrated include: (1) training the classifiers using accelerometer data and testing on laser vibrometer data, (2) combining the data and classifying the vehicle, and (3) different repetitions of these tests with different vehicle states such as idle or revving and varying stationary revolutions per minute (rpm).

Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR V, 2014

This paper evaluates and expands upon the existing end-to-end process used for vibrometry target ... more This paper evaluates and expands upon the existing end-to-end process used for vibrometry target classification and identification. A fundamental challenge in vehicle classification using vibrometry signature data is the determination of robust signal features. The methodology used in this paper involves comparing the performance of features taken from automatic speech recognition, seismology, and structural analysis work. These features provide a means to reduce the dimensionality of the data for the possibility of improved separability. The performances of different groups of features are compared to determine the best feature set for vehicle classification. Standard performance metrics are implemented to provide a method of evaluation. The contribution of this paper is to (1) thoroughly explain the time domain and frequency domain features that have been recently applied to the vehicle classification using laser-vibrometry data domain, (2) build an end-to-end classification pipeline for Aided Target Recognition (ATR) with common and easily accessible tools, and (3) apply feature selection methods to the end-to-end pipeline. The end-to-end process used here provides a structured path for accomplishing vibrometry-based target identification. This paper will compare with two studies in the public domain. The techniques utilized in this paper were utilized to analyze a small in-house database of several different vehicles.

IEEE Transactions on Aerospace and Electronic Systems, 2000

Automatic target recognition (ATR) using high range resolution (HRR) radar signatures is develope... more Automatic target recognition (ATR) using high range resolution (HRR) radar signatures is developed using classical Bayesian multiple hypothesis theory. An eigen-template-based matched filtering (ETMF) algorithm is presented where the templates are formed using the dominant range-space eigenvector of detected HRR training profiles and classification is performed using normalized matched filtering (MF). The proposed approach is extended to multi-look and sequential ATR where new observation profiles are recursively combined probabilistically with previous steps to update ATR results, which is useful for simultaneous recognition and tracking of moving targets. An HRR-specific profile normalization scheme is presented to satisfy matched filter requirements. Classification performance of the proposed method has been compared with a linear least-squares method and hidden Markov model (HMM) approach using MSTAR data collection.

IEEE CONFERENCE ON DECISION AND CONTROL, 1992

Signal and Image Processing, Aug 15, 2006

Abstract: A new class of Subspace filter based algorithms is proposed for detecting targets in fo... more Abstract: A new class of Subspace filter based algorithms is proposed for detecting targets in forest clutter. The training phase “learns” the clutter characteristics using local or global clutter subspaces. Both off-line and on-the-fly self-training versions of the algorithm are developed. These adaptive approaches utilize the Singular Value Decomposition (SVD) algorithm where small blocks of data in the neighborhood of a sliding test window are processed in real-time to estimate clutter characteristics. The clutter models are then used ...

A system and method for spectrum re-use employing transfer domain communications systems is discl... more A system and method for spectrum re-use employing transfer domain communications systems is disclosed. An adaptive waveform technique reconfigures its fundamental modulation waveform depending on the spectral environment. Spectral interference, or other friendly user's presence, is estimated using general spectral estimation techniques. Once the frequency bands containing strong interference or signals of other users are identified, those frequency bands are removed prior to creating a time-domain Fundamental ...

Acoustics, Speech and Signal Processing, IEEE Transactions on, Jun 1, 1986

An explicit connection between fitting exponential models and pole-zero models to observed data i... more An explicit connection between fitting exponential models and pole-zero models to observed data is made. The fitting problem is formulated as a constrained nonlinear minimization problem. This problem is then solved using a simplified iterative algorithm. The algorithm is applied to simulated data, and the performance of the algorithm is compared to previous results.

Circuits, Systems, and Signal Processing, Nov 1, 1994

A theoretical and algorithmic framework is proposed for the identification of rational transfer f... more A theoretical and algorithmic framework is proposed for the identification of rational transfer function matrices of a class of discrete-time multivariable systems. The proposed technique obtains an optimal approximation from the given (possibly noisy) measuredimpulse response data. It is assumed that the measured impulse response data corresponds to a system with a strictly proper transfer function matrix. The impulse response fitting error criterion is theoretically decoupled into a purely linear problem for estimating ...

As the modern electro-magnetic environment in urban and battlefield scenarios becomes increasingl... more As the modern electro-magnetic environment in urban and battlefield scenarios becomes increasingly denser, system designers tend to gravitate toward wide bandwidth solutions. Not only do spread spectrum designs permit increased co-channel utilization, they also tend to be inherently more secure, decreasing the probability of intercept by non-cooperative receivers. This is in part due to the code that must be applied in order to modulate the information bandwidth into a much wider transmitted bandwidth. In addition the non-cooperative receiver must contend with issues of increased noise, decreased sensitivity, and increased signal processing resource requirements among others. The problem is further exacerbated for receivers that must perform emitter geo-location or other forms of spatial processing, since the conventional high-resolution techniques rely on phase measurements based on the monochromatic assumption. This paper will discuss some of the existing methods suggested to contend with wide bandwidth spatial processing for noncooperative receivers and their limitations. It will introduce a new method based on the bilinear transformation that overcomes some of these limitations. It will present simulation results that demonstrate the advantage of this technique.

2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2012

Fourth IEEE Workshop on Sensor Array and Multichannel Processing, 2006., 2006