Signal Source Localization Research Articles

Real-Time Localization of Moving Dipole Sources for Tracking Multiple Free-Swimming Weakly Electric Fish

In order to survive, animals must quickly and accurately locate prey, predators, and conspecifics using the signals they generate. The signal source location can be estimated using multiple detectors and the inverse relationship between the received signal intensity (RSI) and the distance, but difficulty of the source localization increases if there is an additional dependence on the orientation of a signal source. In such cases, the signal source could be approximated as an ideal dipole for simplification. Based on a theoretical model, the RSI can be directly predicted from a known dipole location; but estimating a dipole location from RSIs has no direct analytical solution. Here, we propose an efficient solution to the dipole localization problem by using a lookup table (LUT) to store RSIs predicted by our theoretically derived dipole model at many possible dipole positions and orientations. For a given set of RSIs measured at multiple detectors, our algorithm found a dipole location having the closest matching normalized RSIs from the LUT, and further refined the location at higher resolution. Studying the natural behavior of weakly electric fish (WEF) requires efficiently computing their location and the temporal pattern of their electric signals over extended periods. Our dipole localization method was successfully applied to track single or multiple freely swimming WEF in shallow water in real-time, as each fish could be closely approximated by an ideal current dipole in two dimensions. Our optimized search algorithm found the animal’s positions, orientations, and tail-bending angles quickly and accurately under various conditions, without the need for calibrating individual-specific parameters. Our dipole localization method is directly applicable to studying the role of active sensing during spatial navigation, or social interactions between multiple WEF. Furthermore, our method could be extended to other application areas involving dipole source localization.

TOA-Based Source Localization: A Linearization Approach Adopting Coordinate System Translation

This paper addresses the localization of a timing signal source based on the time of arrival (TOA) measurements that are collected from nearby sensors that are position known and synchronized to each other. Generally speaking, for such TOA-based source localization, the corresponding observation equations contain nonlinear relationship between measurements and unknown parameters, which normally results in the nonexistence of any efficient unbiased estimator that attains the Cramer-Rao lower bound (CRLB). In this paper, we devise a new approach that utilizes linearization and adopts suitable coordinate system translation to eliminate nonlinearity from the converted observation equations. The performance analysis and simulation study conducted show that our proposed algorithm can achieve the CRLB when the zero-mean Gaussian and independent measurement errors are sufficiently small.

Improving LMS/NLMS-Based Beamforming Using Shirvani-Akbari Array

ULA is the most common geometry exp lo ited in array signal processing. In the beamforming operation, em- ploying the ULA leads to obtaining narrower beamwidth with respect to other geometries in similar ele ment numbers. Re- cently, Shirvani and Akbari proposed a new array by adding two elements to the ULA in top and bottom of the array axis, named as SAA. Th is new array offers a considerable imp rovement in DOA estimation performance in detection and resolu- tion of signal sources placed at angles close to the array endfires. In this article, the performance of the proposed SAA is investigated especially in beamforming and co mpared with ULA. LMS and NLMS algorith ms that are popular adaptive beamforming methods are used for evaluation and co mparing the performance of SAA and ULA . Considering array factor, mean square erro r and bit error rate metrics, simu lation results show improved convergence speed and higher data trans- mission accuracy in different signal source locations, boresight angles as well as endfire ones, for SAA with respect to ULA .

A Source Localization Based on Signal Attenuation and Time Delay Estimation in Sensor Networks

The problem of localization in sensor networks, based on both the time delays in signal reception and signal attenuation is considered in this paper. This approach would enhance the localization performance compared to when only phase shifts resulted by time delays or only attenuation information are used. Considering an attenuation model for the signal and taking into account the signal reception delays, a cost function minimization problem is formed. Due to the convergence speed, stability and the advantage of using trust region methods, a Levenberg-Marquardt algorithm is used to find the location of signal sources. Implementation details of the algorithm such as closed form equations to calculate the Jacobian at every iteration are also provided in this paper. At the end, some simulation results would demonstrate the validity of our proposed method. Keywords-sensors, localization, Levenberg-Marquardt algorithm

Analysis of the local lithospheric magnetic activity before and after Panzhihua <i>M</i><sub>w</sub> = 6.0 earthquake (30 August 2008, China)

Abstract. Lithospheric ultra low frequency (ULF) magnetic activity is recently considered as a very promising candidate for application to short-time earthquake forecasting. However the intensity of the ULF lithospheric magnetic field is very weak and often masked by much stronger ionospheric and magnetospheric signals. The study of pre-earthquake magnetic activity before the occurrence of a strong earthquake is a very hard problem which consists of the identification and localization of the weak signal sources in earthquake hazardous areas of the Earth's crust. For the separation and localization of such sources, we used a new polarization ellipse technique (Dudkin et al., 2010) to process data acquired from fluxgate magnetometers installed in the Sichuan province, China. Sichuan is the region of the strongest seismic activity on the territory of China. During the last century, about 40 earthquakes with magnitude M ≥ 6.5 happened here in close proximity to heavy populated zones. The Panzhihua earthquake Mw = 6.0 happened in the southern part of Sichuan province on 30 August 2008 at 8:30:52 UT. The earthquake hypocentre was located at 10 km depth. During the period 30–31 August – the beginning of September 2008, many clustered aftershocks with magnitudes of up to 5.6 occurred near the earthquake epicentre. The data from three fluxgate magnetometers (belonged to China magnetometer network and placed near to the clustered earthquakes at a distance of 10–55 km from main shock epicenter) have been processed. The separation between the magnetometers was in the range of 40–65 km. The analysis of a local lithospheric magnetic activity during the period of January–December 2008 and a possible source structure have been presented in this paper.

Multi-Space Competitive DGA for Model Selection and its Application to Localization of Multiple Signal Sources

In this paper, a new optimization method, which is effective for the problems that the optimum solution should be searched in several solution spaces, is proposed. The proposed method is an extension of Distributed Genetic Algorithm (DGA), in which each subpopulation searches a solution in the corresponding solution space. Through the competition between the sub-populations, population sizes are adequately and gradually changed. By the change of the population size, the appropriate sub-population attracts many individuals. The changing population size yield the efficient search for the problems of searching for solutions in multiple spaces. In order to evaluate the proposed method, it is applied to a polynomial curve fitting and signal source localization, in which the number of sources is preliminarily unknown. Simulation results show the effectiveness of the proposed method.

Selected Papers from NaBIC 2010

The Second World Congress on Nature and Biologically Inspired Computing (NaBIC2010) was held at the Kitakyushu International Conference Center December 15-17, 2010, in Kitakyushu, Japan. NaBIC2010 provided a forum for researchers, engineers, and students from worldwide to discuss state-of-the-art machine intelligence and to address issues related to building human-friendly machines by learning from nature. NaBIC2010 covered a wide range of studies ? from theoretical and algorithmic studies on nature and biologically inspired computing techniques to their real-world applications. Top researchers presenting papers at NaBIC2010 were invited to contribute to this special issue. Through a fair peer review process, four extended papers have been accepted ? an acceptance rate of 50%. The first paper entitled gA Study on Computational Efficiency and Plasticity in Baldwinian Learningh by Liu and Iba analyzes Baldwinian evolution efficiency by comparing it to alternatives such as standard Darwinian evolution with no learning, Lamarckian evolution, and Baldwinian evolution with different learning and plasticity evolution. The second paper entitled gExperimental Study of a Structured Differential Evolution with Mixed Strategiesh by Ishimizu and Tagawa proposes island-based DE with ring or torus networks. The authors examine the performance of the proposed DE with the effects of different strategies. The third paper entitled gMulti-Space Competitive DGA for Model Selection and its Application to Localization of Multiple Signal Sourcesh by Ishikawa, Misawa, Kubota, Tokiwa, Horio, and Yamakawa proposes a distributed genetic algorithm in which each subpopulation searches for a solution in different decision space. Subpopulations change size based on search progress. The fourth paper entitled gAn Extended Interactive Evolutionary Computation Using Heart Rate Variability as Fitness Value for Composing Music Chord Progressh by Fukumoto, Nakashima, Ogawa, and Imai uses heart-rate variability instead of direct human evaluations in an interactive evolutionary computation framework. As guest editors of this special issue, we would like to thank the authors for their unique and interesting contributions and the reviewers for their careful checking and invaluable comments.

SCP Enabled Navigation Using Signals of Opportunity in GPS Obstructed Environments

Spectral Compression Positioning™ (SCP) is an innovative method for deriving positioning, navigation, and timing (PNT) information from Signals of Opportunity (SoOps). The method enables precise PNT in GNSS obstructed environments providing expanded coverage, reliability, and accuracy. This paper introduces the core principles of SCP-based PNT and explores both autonomous and network-based implementation architectures. Providing precise, cost-effective, and autonomous positioning information for navigating indoors or in GPS obstructed environments is a technical challenge that remains largely unsolved. Advances in hybrid Wi-Fi/A-GPS positioning and inertial technologies have yet to deliver meter-level accuracy without the need for custom infrastructure or extensive RF fingerprinting. SCP technology offers a unique alternative approach to current RF-based positioning techniques that readily exploits terrestrial and orbital Signals of Opportunity without the requirement for purpose built infrastructure or a priori knowledge of the signal source location and clock states.

MRI resolution enhancement: How useful are shifted images obtained by changing the demodulation frequency?

Super-resolution reconstruction is a process by which a set of different low resolution images of the same object are used to create an enhanced, higher resolution image of that object. Recently there has been debate amongst researchers whether it is possible to obtain in-plane image enhancement using a set of low resolution magnetic resonance images, acquired by making small, independent changes to the demodulation frequency. We show that shifted low-resolution images contain different information that can be used to obtain denser sampling, leading to image enhancement. We conclude this from specific phantom experiments, applying signal processing sampling theory and taking into consideration the relative sampling of the point spread function with respect to the location of signal sources. Furthermore, the maximum achievable resolution for Fourier encoded MRI data at a boundary or object feature is governed by the effective width of the point spread function or the Fourier pixel size determined by the extent of k-space; this is verified experimentally.

Development of a Highly Sensitive Optically Pumped Atomic Magnetometer for Biomagnetic Field Measurements: A Phantom Study

We developed a highly sensitive optically pumped atomic magnetometer for measuring biomagnetic fields from the human body noninvasively. The sensor head was a cubic Pyrex glass cell containing potassium metal and buffer gases. A pump laser beam for spin-polarizing potassium atoms and a probe laser beam for detecting magneto-optical rotation crossed at right angles in the cell, which was heated in an oven to vaporize potassium atoms. The sensitivity of the magnetometer reached to 10-100 fT/Hz <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1/2</sup> at frequencies below several hundred hertz. To test system performance, we made a phantom which models the human brain, taking into account the contribution of distributed electric currents. First, we tested the phantom by a 306-channel whole-head MEG system and confirmed good agreement of the measured field distributions with theoretical calculations. Subsequently, we measured magnetic field distribution with the phantom scanning two-dimensionally above the oven. The signal source location was estimated by least squares fitting to the measured distribution. The goodness of fit value between the measured and the theoretical distributions was 97.9%.

Use of Ground-Based Signals of Opportunity for Smart Projectile Navigation

Global positioning system (GPS) is a widely accepted means of navigation, whether it is for civilian or military means. With the implementation of GPS on smart projectiles, these weapons have been able to achieve remarkable accuracy. Even though the improvements in accuracy are impressive, GPS signals are susceptible to jamming and spoofing by a sufficiently motivated enemy. The work reported here examines the viability of constructing a navigation solution using ground-based signals of opportunity that provide range and range rate information. Using a generalized sensor model encompassing the key error terms, a variety of physical devices are included in the analysis. For a typical indirect fire trajectory, navigation solutions are computed as a function of the number and density of signal sources, terrain type, and sensor errors. Results indicate that navigation solutions can be computed with the same accuracy as current GPS systems with a moderate number of signal sources. Generally, more accurate solutions are obtained when the projectile is directly over the signal sources and there is a variation of signal source location in all three axes.

도심 환경에서 전파 특성 모의 해석을 위한 신호 독립 부트리 방법에 대한 연구

본 논문에서는 도심과 같이 전기적으로 큰 환경에서 광선 추적법의 광선 추적을 통한 트리 구성 및 부트리 사용에 있어서 부트리 재사용을 통한 트리 생성 효율을 높이기 위해 신호원 독립 부트리 방법을 제안하였다. 신호원 독립 부트리 방법의 적용 결과, 피코셀 및 마이크로셀에서의 노드 개수가 트리 깊이 6에서 100배 감소하는 것을 확인하였으며, 노드 재사용 효율 분석을 통해 송신 위치가 변해도 전체 노드 중 88~98 %가 재사용되는 것을 확인하였다. 그러므로 제안된 신호원 독립 부트리 적용을 통해 광선 추적법 성능 개선은 물론 다중 안테나 또는 기지국 최적화와 같은 다중 송신기 사용 시 노드 재사용으로 인한 성능 개선에 유용하다. In this paper, a SIT(Source Independent Tree) method for ray tracing is proposed to enhance the efficiency of tree construction with reuse of sub tree in urban environment, As the SIT method is applied, the decrease of the number of nodes for picocell and microcell simulations is 100 times. And 88~98 % of the total nodes are reused with change of location of signal source from an analysis of node reuse efficiency. Therefore the proposed SIT method is useful in performance enhancement of ray tracing, especially, for multiple antenna simulation like as MIMO system and cell planning.

Signal source localization by using self-organizing relationship network

It is essential technique to accurately localize a signal source in a brain for successful surgery of intractable epilepsy patients. In order to improve the accuracy of the localization, in this paper, we will introduce a localizing method by using Self-Organnizing Relationship (SOR) network. The SOR network has a feature of realizing an approximation of a desirable input/output relationship of a target system. We think that the feature can be also applied the signal source localizing.

Glowworm swarm optimisation: a new method for optimising multi-modal functions

This paper presents an exposition of a new method of swarm intelligence based algorithm for optimising multi-modal functions. The main objective of using this method is to ensure capture of all local maxima of the function. The application of this method is in the area of multiple signal source location or identification of odour sources and hazardous spills. The method is based upon a dynamic decision domain for each agent in the swarm that decides its direction of movement by the strength of the signal picked up from its neighbours. This is somewhat similar to the luciferin induced glow of a glowworm which is used to attract mates or prey. The brighter the glow more is the attraction. The method is memory-less and gradient free and does not require the knowledge of any global information. Moreover, the method is amenable to robotic implementation. Several illustrative examples are given to show the effectiveness of the method in comparison to existing swarm intelligence algorithms.

10/20, 10/10, and 10/5 systems revisited: Their validity as relative head-surface-based positioning systems

With the advent of multi-channel EEG hardware systems and the concurrent development of topographic and tomographic signal source localization methods, the international 10/20 system, a standard system for electrode positioning with 21 electrodes, was extended to higher density electrode settings such as 10/10 and 10/5 systems, allowing more than 300 electrode positions. However, their effectiveness as relative head-surface-based positioning systems has not been examined. We previously developed a virtual 10/20 measurement algorithm that can analyze any structural MR head and brain image. Extending this method to the virtual 10/10 and 10/5 measurement algorithms, we analyzed the MR images of 17 healthy subjects. The acquired scalp positions of the 10/10 and 10/5 systems were normalized to the Montreal Neurological Institute (MNI) stereotactic coordinates and their spatial variability was assessed. We described and examined the effects of spatial variability due to the selection of positioning systems and landmark placement strategies. As long as a detailed rule for a particular system was provided, it yielded precise landmark positions on the scalp. Moreover, we evaluated the effective spatial resolution of 329 scalp landmark positions of the 10/5 system for multi-subject studies. As long as a detailed rule for landmark setting was provided, 241 scalp positions could be set effectively when there was no overlapping of two neighboring positions. Importantly, 10/10 positions could be well separated on a scalp without overlapping. This study presents a referential framework for establishing the effective spatial resolutions of 10/20, 10/10, and 10/5 systems as relative head-surface-based positioning systems.

Spatial accuracy of fMRI activation influenced by volume- and surface-based spatial smoothing techniques

As improvements in cortical surface modeling allowed accurate cortical topology in brain imaging studies, surface-based methods for the analysis of functional magnetic resonance imaging (fMRI) were introduced to overcome the topological deficiency of commonly used volume-based methods. The difference between the two methods is mainly due to the smoothing techniques applied. For practical applications, the surface-based methods need to quantitatively validate the accuracy of localizing activation. In this study, we evaluated the spatial accuracy of activation detected by the volume- and surface-based methods using simulated blood oxygenation level-dependent (BOLD) signals and MRI phantoms focusing on the influence of their smoothing techniques. T1- and T2-weighted phantoms were acquired from BrainWeb ( http://www.bic.mni.mcgill.ca/brainweb/) and used to extract cortical surfaces and to generate echo planar imaging (EPI) data. Simulated BOLD signals as the gold standard of activation in our experiment were applied to the surfaces and projected to the volume space with random noise. Three-dimensional isotropic Gaussian kernel smoothing and two-dimensional heat kernel smoothing were applied to the volume- and surface-based methods. Sensitivity and 1-specificity, which are truly and falsely detected activations, and similarity measures, which are spatially and statistically similar for the gold standard and detected activations, were calculated. In the results, the surface-based method showed the sensitivity and similarity scores of about 12% higher than the volume-based method. In conclusion, the surface-based method guarantees better spatial accuracy for the localization of BOLD signal sources within the cortex than the volume-based method.

Accuracy of Two-Dipole Source Localization Using a Method Combining BP Neural Network with NLS Method from 32-Channel EEGs

The electroencephalogram (EEG) has become a widely used tool for investigating brain function. Brain signal source localization is a process of inverse calculation from sensor information (electric potentials for EEG) to the identification of multiple brain sources to obtain the locations and orientation parameters. In this paper, we describe a combination of the backpropagation neural network (BPNN) with the nonlinear least-square (NLS) method to localize two dipoles with reasonable accuracy and speed from EEG data computerized by two dipoles randomly positioned in the brain. The trained BPNN, obtains the initial values for the two dipoles through fast calculation and also avoids the influence of noise. Then the NLS method (Powell algorithm) is used to accurately estimate the two dipole parameters. In this study, we also obtain the minimum distance between the assumed dipole pair, 0.8 cm, in order to localize two sources from a smaller limited distance between the dipole pair. The present simulation results demonstrate that the combined method can allow us to localize two dipoles with high speed and accuracy, that is, in 20 seconds and with the position error of around 6.5%, and to reduce the influence of noise.

Applications of beamforming and acoustic holography in an anechoic tank with surface reflections

Recently, our institute, KRISO/KORDI, constructed a small anechoic tank which has an anechoic lining at the four walls and bottom. Because surface reflections still occur, special care must be taken for acoustic measurements and array signal processing, for example, source localization and acoustic holography. In this paper the effects of the surface reflections to the array signal processing methods are investigated. First, estimated errors by both methods are analyzed for various measurement parameters. Beamforming experiments with vertical line arrays are performed. Holographic reconstruction of simple and complex acoustic sources is also performed to compare the true and estimated results.

Generalizing MUSIC and MVDR for Multiple Noncoherent Arrays

We examine the problem of source localization and spatial spectrum estimation using sensor arrays that are noncoherent collections of small, coherent subarrays. The covariance of the signal snapshots at each of the coherent subarrays are functions of, among other things, the signal source locations (or the spatial spectrum). Our approach is to derive functions of the subarray covariance matrices that are close approximations of the signal source locations (or the spatial spectrum). We also show how these functions may be considered generalizations of the multiple signal classification (MUSIC) algorithm and the minimum variance distortionless response (MVDR) criterion, respectively. We demonstrate via simulation that, using this approach and array architecture, it is possible to resolve directional ambiguities.

Stray signal source location in far-field antenna/RCS ranges

Various methods for mapping stray signal sources in far-field antenna/RCS test ranges are summarized. These methods use the quiet-zone field probe data at a single frequency or over a frequency band. Relative merits and drawbacks of the various methods are discussed. It is shown that relatively simple processing of the field-probe data can be used for complete mapping of the stray signal sources.