Vinod V. Reddy

Reduced-Complexity Super-Resolution DOA Estimation with Unknown Number of Sources

When the number of sources is inaccurately estimated, it is well-known that the conventional subspace-based super-resolution direction-of-arrival (DOA) estimation techniques provide inconsistent spatial spectrum, and hence the DOA estimates. In this work, we present a novel technique which provides resolution capability comparable with that of the super-resolution techniques. While the working principle of the proposed technique is similar to that of the minimum-norm algorithm, the algorithm is insensitive to the estimated model-order. Simulation studies show that the proposed technique is advantageous over the use of subspace-based techniques with the number of sources estimated by well-known model order estimation techniques.

Footstep detection and denoising using a single triaxial geophone

In this paper we propose a new footstep detection technique for data acquired using a triaxial geophone. The idea evolves from the investigation of geophone transduction principle. The technique exploits the randomness of neighbouring data vectors observed when the footstep is absent. We extend the same principle for triaxial signal denoising. Effectiveness of the proposed technique for transient detection and denoising are presented for real seismic data collected using a triaxial geophone.

Unambiguous speech DOA estimation under spatial aliasing conditions

With the bandwidth of speech signals extending over several octaves, the spatial Nyquist criterion constrains the microphone array design. Violating this criterion by increasing microphone spacing in order to achieve high resolution introduces ambiguity in identifying the source directions due to the aliasing components. In this work, we investigate the effect of spatial aliasing on the direction-of-arrival (DOA) spectrum due to wideband sources. Noting that the extent of aliasing is frequency dependent, we propose a multi-stage scheme for speech DOA estimation following a subband decomposition. To observe the advantage of this scheme, we verify it with the steered minimum variance distortionless response (STMV) and approximate kernel density estimators. The performance is evaluated with simulations and recorded room impulse responses.

On the use of the quaternion generalized Gaussian distribution for footstep detection

We propose a method to detect human footsteps from a vector-quaternion signal acquired by a tri-axial geophone. The quaternion generalized Gaussian distribution (QGGD) is derived to parameterize variations in the vector-quaternion signal using a shape parameter, quantifying non-Gaussianity and quaternion augmented covariance matrix, quantifying inter-channel correlation. The detection of footsteps is then formulated as binary hypotheses tests in terms of the parameters of the QGGD. The effectiveness of the proposed metrics is evaluated on recorded seismic data.

DOA estimation of wideband sources without estimating the number of sources

In this paper, we propose a new technique to estimate wideband source directions from the sensor snapshots without requiring to know the number of sources present in the scenario. This work is motivated by the fact that the existing model order estimation (number of sources) techniques for wideband source scenario are either inaccurate or computationally expensive. Direction-of-arrival (DOA) estimation is realized using a beamformer framework which imposes nulls in the spatial spectrum along the source directions. The null width along the frequency axis is widened by introducing a new data dependent term into the optimization problem, thus achieving wideband capability. Furthermore, the temporal processing of the data snapshots drastically reduces the number of snapshots required for wideband DOA estimation. The effectiveness of the proposed formulation is studied with simulated experiments.

Insights Into MUSIC-Like Algorithm

In this work, we focus on a recent algorithm [Z. Ying and B. P. Ng, “MUSIC-like DOA Estaimation Without Estimating the Number of Sources,” IEEE Trans. Signal Process., vol. 58, no. 3, pp. 1668–1676, 2010], which is remarked to have multiple signal classification (MUSIC)-like performance without requiring to segregate the signal and noise subspaces. The optimization problem solved by this algorithm in each look direction is analyzed to obtain insights into the working principle of the algorithm. Besides showing the similarity between this algorithm and the MUSIC algorithm, its distinction from the Capons estimator is also highlighted. The bounds for the sole parameter embedded within the optimization problem is also discussed. Simulation results evaluate the performance of the technique in comparison with the MUSIC algorithm.

Polarization-cum-energy metric for footstep detection using vector-sensor

We address the problem of human footstep detection using data recorded by a single tri-axial geophone. It is observed that footstep signature recorded using a vector-sensor is characterized by signal polarization, which, when exploited effectively, has the capability to identify footsteps at increasing source-sensor distances compared to existing techniques. We quantify the effect of signal polarization by fitting a great-arc using spherical linear interpolation (SLERP) to the data vectors after normalization. Furthermore, the signal polarization metric, which provides extended detection range, is combined with signal energy to form a robust polarization-cum-energy metric for efficient detection. Experimental results are presented to substantiate the performance of this technique.

A GMM Post-Filter for Residual Crosstalk Suppression in Blind Source Separation

Existing algorithms employ the Wiener filter to suppress residual crosstalk in the outputs of blind source separation algorithms. We show that, in the context of BSS, the Wiener filter is optimal in the maximum likelihood (ML) sense only for normally-distributed signals. We then propose to model the distribution of speech signals using the Gaussian mixture model (GMM) and then derive a post-filter in the ML sense using the expectation-maximization algorithm. We show that the GMM introduces a probabilistic sample weight that is able to emphasize speech segments that are free of crosstalk components in the BSS output and this results in a better estimate of the post-filter. Simulation results show that the proposed post-filter achieves better crosstalk suppression than the Wiener filter for BSS.

Direction-of-arrival estimation of speech sources under aliasing conditions

Due to practical considerations the microphone spacing is increased to achieve improved resolution by violating the spatial Nyquist criterion. Accompanied aliasing components adversely affect the identifiability of the source direction peaks. We investigate the effect of aliasing on the spatial spectrum of the steered minimum variance distortionless response (STMV) method and propose a novel multi-stage scheme assisted by subband decomposition for suppressing aliasing components. The performance of the proposed technique, evaluated with simulations and recorded room responses, reflects the improvement in the identifiability of accurate source directions under aliasing conditions.

Extending the concept of IIR filtering to array processing using approximate spatial IIR structure

Various array processing techniques applied to uniform linear arrays are involuntarily realized using structures that are analogous to finite impulse response filters. This observation leads to the following question: “can we extend infinite impulse response (IIR) filtering to array processing?”. In this paper, we introduce the concept of IIR array in spatial domain. Note that IIR array here does not mean time-domain IIR filtering for array beamforming which is commonly understood. This paper is dedicated to the study of an alternate approach for array signal processing which defines IIR structure in spatial domain. To illustrate the applicability of the concept of IIR array, we propose a new direction-of-arrival estimation technique as well as a beamformer with the spatial domain IIR array implementation. The performance of the proposed methods are comparable to the existing techniques. These illustrations are intended to introduce a new approach which potentially can offer more degrees of freedom to control the performance of the array and reduce the complexity of the system for a desired performance.