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Optimal Ratio Between Coherent and Orthogonal signals in Sparse MIMO Radar

Optimal Ratio Between Coherent and Orthogonal Signals in Spa...

引用

sensor array and multichannel signal processing workshop

作者： Helin Sun Joseph Tabrikian Hagit Messer Hongyuan Gao School of Electrical and Computer Engineering Ben-Gurion University of the Negev Beer-Sheva ISRAEL College of Information and Communication Engineering Harbin Engineering University Harbin CHINA School of Electrical Engineering Tel Aviv University Tel Aviv ISRAEL

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

This paper addresses the problem of spatial waveform design for collocated multiple-input multiple-output (MIMO) radar systems with sparse antenna arrays. The use of sparse arrays allows to obtain narrower beams and therefore higher angular resolution and accuracy. However, if the spatial waveform is not designed properly, the resulting transmit-receive beam-pattern may suffer from significant sidelobes or ambiguity, which can strongly degrade the estimation performance. The Bayesian Cramer-Rao bound (BCRB), which is commonly used for waveform design, may produce inappropriate results as it considers only local errors and ignores the effect of sidelobes and ambiguity. To overcome this limitation, we propose using the arbitrary test-point transformation Weiss-Weinstein bound (AT-WWB) that was recently proposed, as an optimization criterion. This bound is a simpler and tighter version of the Weiss-Weinstein bound (WWB). This bound is derived for collocated MIMO radar and is minimized with respect to the ratio between coherent and orthogonal signals. The proposed method is demonstrated via simulations, and compared to optimization schemes using the BCRB and the WWB. It is shown that the spatial waveform optimized by AT- WWB exhibits superior performance in terms of direction-of-arrival estimation accuracy.

关键词： Direction-of-arrival estimation Accuracy array signal processing MIMO radar Simulation Estimation Spatial resolution

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Source detection in correlated multichannel signal and noise fields

Source detection in correlated multichannel signal and noise...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： G.O. Karim Electr. & Comput. Eng. Dept. Michigan State Univ. East Lansing MI USA

The problem of detecting the number of sources impinging on an array of sensors has received wide interest in many research problems. In particular, the detection of the number of distinct neural sources using a recording array of closely spaced sensors in the brain is one such application. The special case of transient source signals of unknown waveforms corrupted by Gaussian noise is the focus of this paper. We propose a new approach for solving this problem when no a priori knowledge is given about the neural sources and/or the noise processes. By extending our previous array multiresolution analysis framework for noise suppression, signal detection and identification (Oweiss and Anderson (2000, 2001, 2002)), we show that it is feasible to achieve reasonable source detection performance in moderate to low SNR scenarios.

关键词： sensor arrays array signal processing Sequential analysis Background noise Discrete wavelet transforms Gaussian noise signal detection Electrodes signal processing algorithms Multiresolution analysis

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Blind identification of slightly delayed mixtures

Blind identification of slightly delayed mixtures

引用

ieee workshop on Statistical signal and array processing

作者： G. Chabriel J. Barrere MS / GESSY-ISITV Université de Tlemcen La Valette-du-Var France

We are interested in the separation of N propagating source signals recorded simultaneously by a set of receivers. To solve this "cocktail-party problem", we propose to collect a set of spatially close microphones. On each sensor, signals are received with the same attenuation but with different time delays. The linear memoryless conventional model for source separation is then no longer suitable. However, when time delays are small in comparison with the coherence time of each source, we show that this problem can be simplified building up a particular set of instantaneous mixtures involving derivatives of sources with respect to time. Then, sources can be extracted using second-order methods. The limitations of the method are exposed: we explain what a small delay is and we show that the number of sources cannot exceed 3. The validity of the proposed approach is confirmed by computer simulations. Finally, we apply our method to an experiment where two source signals are extracted from their mixtures observed with two omnidirectional microphones in a normal room.

关键词： sensor arrays Reactive power Delay effects Frequency Attenuation Source separation Microphones Additive noise Propagation delay sensor systems

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A New Hyperspectral Compressed Sensing Method for Efficient Satellite Communications

A New Hyperspectral Compressed Sensing Method for Efficient ...

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sensor array and multichannel signal processing workshop

作者： Chia-Hsiang Lin José M. Bioucas Dias Tzu-Hsuan Lin Yen-Cheng Lin Chi-Hung Kao Department of Electrical Engineering National Cheng Kung University Tainan Taiwan Instituto Superior Técnico Universidade de Lisboa Lisbon Portugal

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

Directly transmitting the huge amount of typical hyperspectral data acquired on satellite to the ground station is inefficient. This paper proposes a new compressed sensing strategy for hyperspectral imagery on spaceborne sensors systems. As the onboard computing/storage resources are limited, e.g., on CubeSat, the measurement strategy should be computationally very light. Furthermore, considering the limited communication bandwidth, a very low sampling rate is desired. Our encoder accounts for these requirements by separately recording the spatial details and the spectral information, both of which essentially require only simple averaging operators. Our measurement strategy naturally induces a reconstruction criterion that can be elegantly interpreted as a well-known fusion problem in satellite remote sensing, allowing the adoption of a convex optimization method for simple and fast decoding. Our method, termed spatial/spectral compressed encoder (SPACE), is experimentally evaluated on real hyperspectral data, showing superior efficacy in terms of both sampling rate and reconstruction accuracy.

关键词： Image sensors Satellites sensor systems Convex functions sensors Decoding Image reconstruction

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Dual-use signal processing for a multiple-sensor system: sonar and optical image processing for underwater obstacle avoidance

Dual-use signal processing for a multiple-sensor system: son...

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ieee sensorS

作者： T.M. Massengill D.M. Wilson Department of Electrical Engineering University of Washington Seattle WA USA

A novel method for streamlining two different signals from sonar and optical sensors into a single signal processing flow to implement an obstacle avoidance algorithm is presented. The processing architecture consists of a custom fabricated analog smoothing array and a microcontroller The combination of these two elements reduces power requirements well below that of a DSP performing a similar algorithm enabling a necessary increase of endurance for an autonomous underwater vehicle (AUV). Both signals utilize the same signal path and the final heading decision is made with the microcontroller through a simple and low-power differencing and accumulation process.

关键词： Optical signal processing Sonar Image processing signal processing algorithms signal processing Optical sensors Microcontrollers Streaming media array signal processing Image motion analysis

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Root-MUSIC based source localization using transmit array interpolation in MIMO radar with arbitrary planar arrays

Root-MUSIC based source localization using transmit array in...

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ieee International workshop on Computational Advances in Multi-sensor Adaptive processing (CAMSAP)

作者： Aboulnasr Hassanien Sergiy A. Vorobyov Yeo-Sun Yoon Joon-Young Park Dept. of ECE University of Alberta Edmonton Canada Samsung Thales Co. Ltd. Software Group Yongin-City Gyeonggi-D Korea

We consider the problem of target localization in MIMO radar with arbitrary planar arrays. A method for mapping a two-dimensional (2D) arbitrary transmit array into a uniform rectangular array or an L-shaped array with uniform element displacement is developed. The uniform structure of the mapped array enables applying the computationally efficient 2D root-MUSIC algorithm for estimating the elevation and azimuth parameters of the targets. The transmit array interpolation is achieved by properly designing the mapping matrix via solving a minmax convex optimization problem. We show that there is a tradeoff between the mapping accuracy within a certain desired 2D spatial sector and the sidelobe levels. The performance of the root-MUSIC for the mapped transmit array is shown to achieve the performance of the root-MUSIC associated with a perfect uniform array of the same shape as the mapped one. Simulation examples are used to validate the effectiveness of the proposed method.

关键词： arrays MIMO radar Vectors Azimuth Radar antennas signal processing

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Improved MUSIC using uniform subarrays

Improved MUSIC using uniform subarrays

引用

ieee workshop on Statistical signal and array processing

作者： G. Scarano G. Panci G. Jacovitti INFOCOM Department Università di Roma La Sapienza Rome Italy

Performance analysis shows the asymptotic optimality of the MUSIC technique applied to bearing estimation problems for a sufficiently large number of sensors and not fully-coherent sources. This implies that a large number of covariance lags has to be computed; moreover the computational load of the eigendecomposition of large covariance matrices may be too severe for practical applications. With reference to uniformly spaced linear arrays (ULAs) we show that the accuracy gain associated to an increased number of sensors can be alternatively obtained by applying the MUSIC technique to particular configurations of pairs of ULAs, referenced to as subarrays, using a significantly smaller number of sensors. It is also shown that the accuracy loss of the proposed method, w.r.t. a full ULA covering the same array aperture, can be minimized by varying the distance between the two subarrays. The provided simulation results shows the applicability of the proposed method.

关键词： Multiple signal classification sensor arrays Covariance matrix Performance analysis Apertures Yield estimation Direction of arrival estimation array signal processing Guidelines Prediction methods

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A Unified Approach for Target Direction Finding Based on Convolutional Neural Networks

A Unified Approach for Target Direction Finding Based on Con...

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ieee workshop on Machine Learning for signal processing

作者： Chong Wang Wei Liu Mengdi Jiang Faculty of Electrical Engineering and Computer Science Ningbo University China The University of Sheffield UK

ISBN: (数字)9781728166629

ISBN: (纸本)9781728166636

A convolutional neural network (CNNs) based approach for target direction finding with the thinned coprime array (TCA) as an example is proposed. The ResNeXt network is adopted as the backbone network with a multi-label classification modification to find directions of an unknown number of targets. Unlike the traditional wisdom, where an additional co-array operation is needed for underdetermined direction finding (the number of sources is larger than the number of physical sensors), in the proposed approach, it is shown that the same network with raw data as its input can deal with both the overdetermined and underdetermined cases, although using covariance matrix of the data can reduce the complexity of the whole training process at the cost of estimation performance.

关键词： sensor arrays sensors Training Covariance matrices array signal processing Entropy Convolutional neural networks

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Multi-target tracking with stored program adaptive CNN universal machines

Multi-target tracking with stored program adaptive CNN unive...

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ieee International workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： C. Rekeczky G. Timar G. Cserey Analogical and Neural Computing Systems Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

This paper shows that the performance of multi-target tracking (MTT) systems can be significantly increased with stored program adaptive cellular array sensors. The primary motivation of the present work is to define a topographic microprocessor architecture for MTT with embedded sensors capable of operating in a process real-time manner. In the ongoing experiments it is assumed that the input data flow is acquired by a single array sensor and the data is processed on an adaptive CNN-UM architecture consisting of both a cellular nonlinear network (CNN) and digital signal processing (DSP) microprocessors. The algorithms designed for this combined hardware platform use adaptive multi-channel CNN solutions for instantaneous position estimation and morphological characterization of all visible targets and the DSP environment for distance calculation, gating, data association, track maintenance and dynamic target motion prediction. A special feature of the architecture is that it allows interactive communication between the sensor and the digital environment. The configuration of functional modules for various real-time applications is discussed. Using real-life video-flows, successful tracking of several maneuvering targets is demonstrated within the proposed adaptive multi-channel framework.

关键词： Cellular neural networks Turing machines sensor arrays Digital signal processing Adaptive arrays Microprocessors sensor phenomena and characterization Target tracking sensor systems Cellular networks

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Energy-Based Position Estimation of Microphones and Speakers for Ad Hoc Microphone arrays

Energy-Based Position Estimation of Microphones and Speakers...

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ieee workshop on Applications of signal processing to Audio and Acoustics

作者： Minghua Chen Zicheng Liu Li-Wei He Phil Chou Zhengyou Zhang Microsoft Research Limited Redmond WA USA

We present a novel energy-based algorithm to estimate the positions of microphones and speakers in an ad hoc microphone array setting. Compared to traditional time-of-flight based approaches, energy-based approach has the advantage that it does not require accurate time synchronization. This property is particularly useful for ad hoc microphone arrays because highly accurate synchronization across microphones may be difficult to obtain since these microphones usually belong to different devices. This new algorithm extends our previous energy-based position estimation algorithm [1] in that it does not assume the speakers are in the same positions as their corresponding microphones. In fact, our new algorithm estimates both the microphones and speakers simultaneously. Experiment results are shown to demonstrate its performance improvement over the previous approach in [1], and evaluate its robustness against time synchronization errors.

关键词： Microphone arrays Loudspeakers signal processing algorithms sensor arrays Cameras array signal processing Robustness Geometry Delay effects Portable computers

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