Left-right Ambiguity Research Articles

Resolution of Left-Right Ambiguity for Underwater Bearing Only Tracking

Resolution of Left-Right Ambiguity for Underwater Bearing Only Tracking

KinKal: A Kinematic Kalman filter Track Fitting Package for the Mu2e Experiment

Many current physics experiments require precision reconstruction of low-energy particles. One example is the Mu2e experiment, which requires reconstructing an isolated 105 MeV electron with better than 500 KeV/c momentum resolution. Mu2e uses a low-mass straw tube tracker, and a CsI crystal calorimeter, to reconstruct tracks. In this paper, we present the design and performance of a track reconstruction algorithm optimized for Mu2e’s unusual requirements. The algorithm is based on the KinKal [1] kinematic Kalman filter track fit package. KinKal supports multiple track parameterizations, including one optimized for looping tracks, such as Mu2e signal tracks, and others optimized for straight or slightly-curved tracks, such as the high-momentum (>1 GeV/c) cosmic ray muons used to calibrate and align the Mu2e detectors. All KinKal track parameterizations include the track origin time, to correctly model correlations arising from measurements that couple time and space, such as the straw drift time or the calorimeter cluster time. KinKal employs magnetic field inhomogeneity and material effect correction algorithms with 10−4 fractional precision. The Mu2e fit uses Artificial Neural Net functions to discriminate background hits from signal hits, and to resolve the straw tube hit left-right ambiguity, while iterating the extended Kalman filter. The efficiency, accuracy, and precision of the Mu2e track reconstruction, as tested on detailed simulations of Mu2e data, are presented.

Left-Right ambiguity resolution for coprime sparse arrays.

Coprime Sparse Arrays (CSA) with two collocated uniform linear arrays are used to estimate O(MN) direction of arrivals for a narrow band source with only O(M+N) sensors. The CSA cannot discriminate the azimuth and its complementary angles due to the symmetry along the array-axis. The bearing ambiguity, also referred to as a Left-Right (LR) ambiguity, is addressed in this paper using CSA. We design Left-Right resolved Coprime Sparse Arrays (LRCSA) to produce a null that is electronically steered to the complementary angle of the desired direction. LRCSA twin array achieves higher spatial resolution than the conventional fully populated LR array with same number of sensors, much like the collocated CSA. Three methods, namely, Null Constrained Beamformer (NCB), two-dimensional Direct Beamformer (2DDB), and LRCSA are studied. The bound on the detection gain is analytically established for the LRCSA under correlated noise scenarios modeled by the first-order autoregressive process. Twin array processing using the LRCSA method results in narrow mainlobe beam width along with a higher rejection ratio (RR) compared to 2DDB and NCB. Data obtained from a sea experiment using a towed array is analyzed. The results confirm that the CSA based cardioid processing resolved LR ambiguity along with a higher RR and narrower beams.

Enhanced Pulsed-Source Localization with 3 Hydrophones: Uncertainty Estimates

The uncertainty behavior of an enhanced three-dimensional (3D) localization scheme for pulsed sources based on relative travel times at a large-aperture three-hydrophone array is studied. The localization scheme is an extension of a two-hydrophone localization approach based on time differences between direct and surface-reflected arrivals, an approach with significant advantages, but also drawbacks, such as left-right ambiguity, high range/depth uncertainties for broadside sources, and high bearing uncertainties for endfire sources. These drawbacks can be removed by adding a third hydrophone. The 3D localization problem is separated into two, a range/depth estimation problem, for which only the hydrophone depths are needed, and a bearing estimation problem, if the hydrophone geometry in the horizontal is known as well. The refraction of acoustic paths is taken into account using ray theory. The condition for existence of surface-reflected arrivals can be relaxed by considering arrivals with an upper turning point, allowing for localization at longer ranges. A Bayesian framework is adopted, allowing for the estimation of localization uncertainties. Uncertainty estimates are obtained through analytic predictions and simulations and they are compared against two-hydrophone localization uncertainties as well as against two-dimensional localization that is based on direct arrivals.

Optimization of Shell packaging for cilium MEMS bionic vector hydrophone

Packaging of vector hydrophone influences its engineering application scope. However, the sensitivity of vector hydrophone is greatly reduced after packaging in previous works. Moreover, the vector hydrophone with dipole directivity has the problem of left-right ambiguity. To solve these problems, the shell packaging of cilium MEMS bionic vector hydrophone is optimized in terms of sound-transparent cap and the capability of underwater localization. A blue nitrile butadiene rubber is used as the material for the sound-transparent cap to solve the problem of poor sensitivity after packaging. And in order to solve the problem of left-right ambiguity of a single vector hydrophone, a piezoelectric ceramic tube is integrated into the shell to obtain sound pressure information. In this paper, the packaging process of optimized shell is introduced in detail. Then, the sensitivity test, directivity test and pressure-resisting test of optimized shell are finished. The testing results show that sensitivity of vector information part is increased average 5.6 dB after packaging. And the sensitivity curve depicts that the sensitivity increases 6 dB per octave in the working bandwidth in the range of 63−1000 Hz. Therefore, the optimized vector hydrophone shows a good performance in engineering application.

Array MEMS Vector Hydrophone Oriented at Different Direction Angles

A new type of array MEMS (Microelectro Mechanical Systems) vector hydrophone has been proposed to solve the left-right ambiguity problem that is commonly found in current ones. Meanwhile, the advantages of good sensitivity and low fabrication cost are maintained. The array MEMS vector hydrophone is integrated by four units oriented at different direction angles. By the aid of this kind of vector hydrophone, not only the exact direction of the sound source can be measured, but also the position obtained. The working principle of the array microstructure has been analyzed and simulated. The result shows that the position of the sound source can be well determined. The prototype of the hydrophone is fabricated based on standard MEMS technology, and its performance is tested in a standing wave tube and an anechoic tank. The testing results show that the array hydrophone exhibits a good consistency of all the four units and satisfactory performance. More importantly, this array hydrophone exhibits excellent ability of positioning with the relatively small angle error. Thus, a MEMS hydrophone with multiple functions and relatively high performance is realized, which has important theoretical and practical significance in relevant applications such as the small-size underwater vehicles.

Microlocal analysis of Doppler synthetic aperture radar

We study the existence and suppression of artifacts for a Doppler-based Synthetic Aperture Radar (DSAR) system. The idealized air- or space-borne system transmits a continuous wave at a fixed frequency and a co-located receiver measures the resulting scattered waves; a windowed Fourier transform then converts the raw data into a function of two variables: slow time and frequency. Under simplifying assumptions, we analyze the linearized forward scattering map and the feasibility of inverting it via filtered backprojection, using techniques of microlocal analysis which robustly describe how sharp features in the target appear in the data. For DSAR with a straight flight path, there is, as with conventional SAR, a left-right ambiguity artifact in the DSAR image, which can be avoided via beam forming to the left or right. For a circular flight path, the artifact has a more complicated structure, but filtering out echoes coming from straight ahead or behind the transceiver, as well as those outside a critical range, allows one to obtain an artifact-free image. Initially derived under a start-stop approximation widely used in range-based SAR, we show that some of these results are robust and hold under a more realistic approximation.

Experimental extreme high‐squint SAR target imaging

An experimental study of extreme high-squint (i.e. forward-looking) synthetic aperture radar (SAR) is presented. Experimental data collected against a distributed complex target are successfully focused using the backprojection algorithm. Interferometric SAR processing is then performed in order to overcome left-right ambiguity and estimate constituent scatterer Cartesian coordinates.

Bearing and range tracking with a two-hydrophone ocean glider

A Slocum glider fitted with two hydrophones separated by a distance of approximately 3 feet recorded sperm whale sounds during an experiment off the west coast of the island of Sardinia, Italy, in the summer of 2014. Time difference of arrival analysis of their echolocation clicks provided bearing tracks. It was also found that the left-right ambiguity inherent of the bearing estimation process could be broken by the natural oscillation in glider heading. More recently, a controlled experiment on a quiet lake with a known fixed acoustic source was devised to investigate unambiguous bearing estimation and possible ranging. Simple target motion analysis (TMA) using the glider’s position data resulted in range estimates of only a few hundred meters short of the true source location. Analysis of the acoustic data on the other hand, presented challenges to satisfactory TMA performance. Overall, it was found that simple bearing-only TMA analysis is possible with two-hydrophone acoustic data and small angular change of a few degrees in the heading of the observing platform. Results will be discussed with implications to marine mammal population density estimation studies, since the ability to estimate direction and range of sound-producing animals could improve estimation of detection probabilities.

Underwater acoustic localization of sperm whales with a pair of hydrophones

An iterative Bayesian approach using a pair of hydrophones was applied for the localization of vocalizing (click producing) sperm whales off the southern coast of Crete in the Eastern Mediterranean Sea in June 2015. The localization method relies on the time difference between direct and surface reflected arrivals at each hydrophone as well as between the direct arrivals at the two hydrophones, and on the knowledge of the hydrophones depths, whereas it accounts for refraction due to a depth-dependent sound-speed profile. The method provides range and depth estimates as well as estimates for the localization uncertainty reflecting measurement errors and environmental uncertainties. Further, by assuming a simple model for the array geometry bearing estimates were obtained. The inherent left-right ambiguity in bearing estimation can be resolved by changing the array orientation through maneuvering. The localization results were verified through encounters with the sperm whales when they ascended to the surface. [Work supported by EU-Greece through the Aristeia-II program and the NSRF 2014-2020/PERAN project.]

Human Pose and Path Estimation from Aerial Video Using Dynamic Classifier Selection

We consider the problem of estimating human pose and trajectory by an aerial robot with a monocular camera in near real time. We present a preliminary solution whose distinguishing feature is a dynamic classifier selection architecture. In our solution, each video frame is corrected for perspective using projective transformation. Then, two alternative feature sets are used: (i) Histogram of Oriented Gradients (HOG) of the silhouette, (ii) Convolutional Neural Network (CNN) features of the RGB image. The features (HOG or CNN) are classified using a dynamic classifier. A class is defined as a pose-viewpoint pair, and a total of 64 classes are defined to represent a forward walking and turning gait sequence. Our solution provides three main advantages: (i) Classification is efficient due to dynamic selection (4-class vs. 64-class classification). (ii) Classification errors are confined to neighbors of the true view-points. (iii) The robust temporal relationship between poses is used to resolve the left-right ambiguities of human silhouettes. Experiments conducted on both fronto-parallel videos and aerial videos confirm our solution can achieve accurate pose and trajectory estimation for both scenarios. We found using HOG features provides higher accuracy than using CNN features. For example, applying the HOG-based variant of our scheme to the 'walking on a figure 8-shaped path' dataset (1652 frames) achieved estimation accuracies of 99.6% for viewpoints and 96.2% for number of poses.

Target response analysis for forward‐looking SAR with simultaneous cross‐track transceiver translation

Theoretical imaging performance for forward-looking synthetic aperture radar (SAR) with simultaneous cross-track transceiver translation is characterised. Cross-range resolution as a function of transceiver transverse velocity and synthetic aperture length is analysed. Then the transverse velocity needed to avoid left-right ambiguity is derived. Lastly, imaging performance is demonstrated by focusing simulated data.

Human motion analysis from UAV video

PurposeThe purpose of this paper is to present a preliminary solution to address the problem of estimating human pose and trajectory by an aerial robot with a monocular camera in near real time.Design/methodology/approachThe distinguishing feature of the solution is a dynamic classifier selection architecture. Each video frame is corrected for perspective using projective transformation. Then, a silhouette is extracted as a Histogram of Oriented Gradients (HOG). The HOG is then classified using a dynamic classifier. A class is defined as a pose-viewpoint pair, and a total of 64 classes are defined to represent a forward walking and turning gait sequence. The dynamic classifier consists of a Support Vector Machine (SVM) classifier C64 that recognizes all 64 classes, and 64 SVM classifiers that recognize four classes each – these four classes are chosen based on the temporal relationship between them, dictated by the gait sequence.FindingsThe solution provides three main advantages: first, classification is efficient due to dynamic selection (4-class vs 64-class classification). Second, classification errors are confined to neighbors of the true viewpoints. This means a wrongly estimated viewpoint is at most an adjacent viewpoint of the true viewpoint, enabling fast recovery from incorrect estimations. Third, the robust temporal relationship between poses is used to resolve the left-right ambiguities of human silhouettes.Originality/valueExperiments conducted on both fronto-parallel videos and aerial videos confirm that the solution can achieve accurate pose and trajectory estimation for these different kinds of videos. For example, the “walking on an 8-shaped path” data set (1,652 frames) can achieve the following estimation accuracies: 85 percent for viewpoints and 98.14 percent for poses.

Realization of a composite MEMS hydrophone without left-right ambiguity

A sound-pressure sound-pressure-gradient composite MEMS vector hydrophone has been proposed and demonstrated to solve the problem of left-right ambiguity that is intrinsic to existing MEMS hydrophones measuring the pressure gradient of a vector sound field. A newly-designed capacitance scalar microstructure is added into a MEMS vector hydrophone that otherwise consists of only a regular cilium-four-beam microstructure. Theoretical model shows that the left-right ambiguity problem can be artfully solved by synthesizing the output signals from the vector and scalar structures. The hydrophone’s ability of azimuth measurement is tested with a standing-wave tube and the error of direction of arrival (DOA) estimation is within 1°. Moreover, the composite hydrophone remains the frequency response trend of the cilium MEMS vector hydrophone. We believe that this work is a significant advance in the development of MEMS hydrophone and should place a solid base for relevant engineering applications.

Analysis of marine mammal bearing tracks from two-hydrophone recordings made with a glider

An underwater glider fitted with two hydrophones recorded approximately 19 hours of data during an opportunistic sea experiment in the summer of 2014. The acoustic data were collected with a sampling frequency of 96 kHz and 16-bit resolution in deep waters off the western coast of the island of Sardinia, Mediterranean Sea. Detection and classification of sounds by a trained human analyst indicated the presence of sperm whale (Physeter macrocephalus) regular clicks as well as dolphin clicks and whistles. A period of 90 min during which the glider did not surface, and which contained extensive sperm whale clicking activity was chosen for analysis. Cross-correlation of the data from both channels allowed the estimation of the direction (bearing) of clicks, and realization of animal tracks. Several bearing tracks were observed through this analysis, closely following the oscillatory pattern of the glider’s heading, suggesting that such information has the potential to break the left-right ambiguity of the bearing estimates. Results from the bearing tracking analysis, including accuracy and performance, will be shown followed by a discussion on how they can aid in population density estimation studies.

Estimating the location of baleen whale calls using dual streamers to support mitigation procedures in seismic reflection surveys.

In order to mitigate against possible impacts of seismic surveys on baleen whales it is important to know as much as possible about the presence of whales within the vicinity of seismic operations. This study expands on previous work that analyzes single seismic streamer data to locate nearby calling baleen whales with a grid search method that utilizes the propagation angles and relative arrival times of received signals along the streamer. Three dimensional seismic reflection surveys use multiple towed hydrophone arrays for imaging the structure beneath the seafloor, providing an opportunity to significantly improve the uncertainty associated with streamer-generated call locations. All seismic surveys utilizing airguns conduct visual marine mammal monitoring surveys concurrent with the experiment, with powering-down of seismic source if a marine mammal is observed within the exposure zone. This study utilizes data from power-down periods of a seismic experiment conducted with two 8-km long seismic hydrophone arrays by the R/V Marcus G. Langseth near Alaska in summer 2011. Simulated and experiment data demonstrate that a single streamer can be utilized to resolve left-right ambiguity because the streamer is rarely perfectly straight in a field setting, but dual streamers provides significantly improved locations. Both methods represent a dramatic improvement over the existing Passive Acoustic Monitoring (PAM) system for detecting low frequency baleen whale calls, with ~60 calls detected utilizing the seismic streamers, zero of which were detected using the current R/V Langseth PAM system. Furthermore, this method has the potential to be utilized not only for improving mitigation processes, but also for studying baleen whale behavior within the vicinity of seismic operations.

Double-constraint flexible tree search-based orthogonal matching pursuit for DOA estimation using dynamic sensor arrays

ABSTRACTGreedy algorithms have leveraged sparse signal models for parameter estimation purposes in applications including bearing estimation and direction-of-arrival (DOA) estimation. A dictionary whose elements correspond to observations for a sampling of the angle space is used for sparse approximation of the received signals; the resulting sparse coefficient vector’s support identifies the DOA estimates. Increasing the angle space sampling resolution provides better sparse approximations for arbitrary observations, while the resulting high dictionary coherence hampers the performance of standard sparse approximation, preventing accurate DOA estimation. To alleviate this shortcoming, in the each iteration, we use the structured sparsity model that keeps high coherent and close spacing dictionary elements. Besides, the proposed approach allows exploitation of the array orientation diversity (achievable via array dynamics) in the compressive sensing framework to address challenging array signal processing problems such as left-right ambiguity and poor estimation performance. And the simulation results show that our proposed algorithm can offer significantly improved performance in single-snapshot scenario with multiple sources.

Prototype of a linear array on an autonomous surface vehicle for the register of dolphin displacement patterns within a shallow bay

A semi-resident population of tursiops has been reported in the south of La Paz bay in Baja California Sur, Mexico, where specific zones for social, feeding and resting behaviors have been detected. Nevertheless, increasing human activities and new constructions are attributed to have shifted the areas of their main activity. Therefore, it becomes important to study displacement patterns of dolphins within the bay and their spatial relationship to maritime traffic and other sources of anthropogenic noise. A prototype of an Autonomous Surface Vehicle (ASV) designed for shallow water bathymetry has been adapted to carry a linear array of hydrophones previously reported for the localization of dolphins from their whistles. Conventional beam-forming algorithms and electrical steering are used to find Direction of Arrival (DOA) of the sound sources. The left-right ambiguity typical of a linear array and front-back lobes for sound sources located at end-fire can be resolved by the trajectory of the ASV. Geo-referenced positions and bearing of the array, provided by the Inertial Measurement Unit of the ASV, along with DOA for various positions allows triangulating and mapping the sound sources. Results from both, controlled experiments using geo-referenced know sources, and field trials within the bay, are presented.

Spatial Compressive Sensing for Direction-of-Arrival Estimation of Multiple Sources using Dynamic Sensor Arrays

This work addresses the problem of direction-of-arrival (DOA) estimation of multiple sources using short and dynamic sensor arrays. We propose to utilize compressive sensing (CS) theory to reconstruct the high-resolution spatial spectrum from a small number of spatial measurements. Motivated by the physical structure of the spatial spectrum, we model it as a sparse signal in the wavenumber-frequency domain, where the array manifold is proposed to serve as a deterministic sensing matrix. The proposed spatial CS (SCS) approach allows exploitation of the array orientation diversity (achievable via array dynamics) in the CS framework to address challenging array signal processing problems such as left-right ambiguity and poor estimation performance at endfire. The SCS is conceptually different from well-known classical and subspace-based methods because it provides high azimuth resolution using a short dynamic linear array without restricting requirements on the spatial and temporal stationarity and correlation properties of the sources and the noise. The SCS approach was shown to outperform current superresolution and orientation diversity based methods in single-snapshot simulations with multiple sources.

Connectivity based human body modeling from monocular camera

In this paper, we develop a system for automated human body tracking and modeling based on a monocular camera. In this system, ten body parts including head, torso, arms and legs are extracted to build a 2D human body model. One way to decompose human silhouette into different parts is to generate cuts between the negative minimum curvature (NMC) points. However, due to the self-occlusion problem and left-right ambiguity, each individual body part cannot be successfully identified in every frame. Therefore, in addition to utilizing the NMC points, we design a forward and backward tracking mechanism to identify the location of head in each frame. The torso angle and size are determined by integrating multiple-frame information with the modified solution of Poisson equation. Hands and feet can then be identified correctly based on a modified star skeleton approach along with the nearest-neighbor tracking mechanism. The rest of joint points can also be located by making use of the notion “connectivity”. In the experiments, we analyze the performance of the proposed human body modeling mechanism. We also demonstrate a behavior analysis application by employing the proposed method. The experiment results verify the robustness of the proposed approach and the feasibility of the employing the proposed approach to the action recognition application.