Robust Detection of Moving Human Target Behind Wall via Impulse through-Wall Radar

Through-wall human target detection is highly desired in military applications. We have developed an impulse through-wall radar (TWR) to address this problem. In order to obtain a robust detection performance, firstly we adopt the exponential average background subtraction (EABS) method to mitigate clutters and improve the signal-to-clutter ratio (SCR). Then, different from the conventional constant false alarm rate (CFAR) methods that are applied along the fast-time dimension, we propose a new CFAR method along the slow-time dimension to resist the residual clutters in the clutter mitigation output because of timing jitters, based on the presence of a larger relative variation of human target moving in and out in comparison with that of residual clutters in the slow-time dimension. The proposed method effectively solves the false alarm issue caused by residual clutters in the conventional CFAR methods, and obtains robust detection performance. Finally, different through-wall experiments are provided to verify the proposed method.Defence Science Journal, 2013, 63(6), pp.636-642, DOI:http://dx.doi.org/10.14429/dsj.63.576

Estimation and tracking of rapidly time-varying broadband acoustic communication channels

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2006This thesis develops methods for estimating wideband shallow-water acoustic communication channels. The very shallow water wideband channel has three distinct features: large dimension caused by extensive delay spread; limited number of degrees of freedom (DOF) due to resolvable paths and inter-path correlations; and rapid fluctuations induced by scattering from the moving sea surface. Traditional LS estimation techniques often fail to reconcile the rapid fluctuations with the large dimensionality. Subspace based approaches with DOF reduction are confronted with unstable subspace structure subject to significant changes over a short period of time. Based on state-space channel modeling, the first part of this thesis develops algorithms that jointly estimate the channel as well as its dynamics. Algorithms based on the Extended Kalman Filter (EKF) and the Expectation Maximization (EM) approach respectively are developed. Analysis shows conceptual parallels, including an identical second-order innovation form shared by the EKF modification and the suboptimal EM, and the shared issue of parameter identifiability due to channel structure, reflected as parameter unobservability in EKF and insufficient excitation in EM. Modifications of both algorithms, including a two-model based EKF and a subspace EM algorithm which selectively track dominant taps and reduce prediction error, are proposed to overcome the identifiability issue. The second part of the thesis develops algorithms that explicitly find the sparse estimate of the delay-Doppler spread function. The study contributes to a better understanding of the channel physical constraints on algorithm design and potential performance improvement. It may also be generalized to other applications where dimensionality and variability collide.Financial support for this thesis research was provided by the Office of Naval Research and the WHOI Academic Program Office

Entanglement Stabilization using Parity Detection and Real-Time Feedback in Superconducting Circuits

Fault tolerant quantum computing relies on the ability to detect and correct errors, which in quantum error correction codes is typically achieved by projectively measuring multi-qubit parity operators and by conditioning operations on the observed error syndromes. Here, we experimentally demonstrate the use of an ancillary qubit to repeatedly measure the $ZZ$ and $XX$ parity operators of two data qubits and to thereby project their joint state into the respective parity subspaces. By applying feedback operations conditioned on the outcomes of individual parity measurements, we demonstrate the real-time stabilization of a Bell state with a fidelity of $F\approx 74\%$ in up to 12 cycles of the feedback loop. We also perform the protocol using Pauli frame updating and, in contrast to the case of real-time stabilization, observe a steady decrease in fidelity from cycle to cycle. The ability to stabilize parity over multiple feedback rounds with no reduction in fidelity provides strong evidence for the feasibility of executing stabilizer codes on timescales much longer than the intrinsic coherence times of the constituent qubits.Comment: 12 pages, 10 figures. Update: Fig. 5 correcte

Single- and multi-microphone speech dereverberation using spectral enhancement

In speech communication systems, such as voice-controlled systems, hands-free mobile telephones, and hearing aids, the received microphone signals are degraded by room reverberation, background noise, and other interferences. This signal degradation may lead to total unintelligibility of the speech and decreases the performance of automatic speech recognition systems. In the context of this work reverberation is the process of multi-path propagation of an acoustic sound from its source to one or more microphones. The received microphone signal generally consists of a direct sound, reflections that arrive shortly after the direct sound (commonly called early reverberation), and reflections that arrive after the early reverberation (commonly called late reverberation). Reverberant speech can be described as sounding distant with noticeable echo and colouration. These detrimental perceptual effects are primarily caused by late reverberation, and generally increase with increasing distance between the source and microphone. Conversely, early reverberations tend to improve the intelligibility of speech. In combination with the direct sound it is sometimes referred to as the early speech component. Reduction of the detrimental effects of reflections is evidently of considerable practical importance, and is the focus of this dissertation. More specifically the dissertation deals with dereverberation techniques, i.e., signal processing techniques to reduce the detrimental effects of reflections. In the dissertation, novel single- and multimicrophone speech dereverberation algorithms are developed that aim at the suppression of late reverberation, i.e., at estimation of the early speech component. This is done via so-called spectral enhancement techniques that require a specific measure of the late reverberant signal. This measure, called spectral variance, can be estimated directly from the received (possibly noisy) reverberant signal(s) using a statistical reverberation model and a limited amount of a priori knowledge about the acoustic channel(s) between the source and the microphone(s). In our work an existing single-channel statistical reverberation model serves as a starting point. The model is characterized by one parameter that depends on the acoustic characteristics of the environment. We show that the spectral variance estimator that is based on this model, can only be used when the source-microphone distance is larger than the so-called critical distance. This is, crudely speaking, the distance where the direct sound power is equal to the total reflective power. A generalization of the statistical reverberation model in which the direct sound is incorporated is developed. This model requires one additional parameter that is related to the ratio between the direct sound energy and the sound energy of all reflections. The generalized model is used to derive a novel spectral variance estimator. When the novel estimator is used for dereverberation rather than the existing estimator, and the source-microphone distance is smaller than the critical distance, the dereverberation performance is significantly increased. Single-microphone systems only exploit the temporal and spectral diversity of the received signal. Reverberation, of course, also induces spatial diversity. To additionally exploit this diversity, multiple microphones must be used, and their outputs must be combined by a suitable spatial processor such as the so-called delay and sum beamformer. It is not a priori evident whether spectral enhancement is best done before or after the spatial processor. For this reason we investigate both possibilities, as well as a merge of the spatial processor and the spectral enhancement technique. An advantage of the latter option is that the spectral variance estimator can be further improved. Our experiments show that the use of multiple microphones affords a significant improvement of the perceptual speech quality. The applicability of the theory developed in this dissertation is demonstrated using a hands-free communication system. Since hands-free systems are often used in a noisy and reverberant environment, the received microphone signal does not only contain the desired signal but also interferences such as room reverberation that is caused by the desired source, background noise, and a far-end echo signal that results from a sound that is produced by the loudspeaker. Usually an acoustic echo canceller is used to cancel the far-end echo. Additionally a post-processor is used to suppress background noise and residual echo, i.e., echo which could not be cancelled by the echo canceller. In this work a novel structure and post-processor for an acoustic echo canceller are developed. The post-processor suppresses late reverberation caused by the desired source, residual echo, and background noise. The late reverberation and late residual echo are estimated using the generalized statistical reverberation model. Experimental results convincingly demonstrate the benefits of the proposed system for suppressing late reverberation, residual echo and background noise. The proposed structure and post-processor have a low computational complexity, a highly modular structure, can be seamlessly integrated into existing hands-free communication systems, and affords a significant increase of the listening comfort and speech intelligibility

Optimal Design and Operational Monitoring of Wind Turbine Blades

The wind turbine blade is a critical component of any wind energy system. Its design, testing, and performance monitoring play a key role in power generation. With the increased use of composites and longer blades, a need to review existing monitoring sensors and use emergent novel ones is urgent among industry practitioners. In addition, an overview relating blade testing to Campbell diagrams and non-contact sensors have not been addressed as part of blade optimization. Based on design loads under IEC 61400-23 standards, the chapter explores various contact and non-contact sensors for design validation as well as their exploratory use in a three-tier structural health monitoring (SHM) framework for blade’s operational performance monitoring. The chapter also includes a case study in the non-contact use of ground-based radar (GBR) in the optimal design of blades and real-time in-field monitoring using condition parameters. Lastly, the chapter addresses the lack of practical guidelines in the complementary use of GBR within a 3-tier SHM framework. Such use has the intent of building a cohesive understanding of GBR use for blade optimization and operational monitoring