Underwater Target Localization Research Articles

An Improved Underwater Electric Field-Based Target Localization Combining Subspace Scanning Algorithm And Meta-EP PSO Algorithm

In this paper, we propose an improved three-dimensional underwater electric field-based target localization method. This method combines the subspace scanning algorithm and the meta evolutionary programming (meta-EP) particle swarm optimization (PSO) algorithm. The subspace scanning algorithm is applied as the evaluation function of the electric field-based underwater target locating problem. The meta-EP PSO method is used to select M elite particles by the q-tournament selection method, which could effectively reduce the computational complexity of the three-dimensional underwater target localization. Moreover, the proposed meta-EP PSO optimization algorithm can avoid subspace scanning trapping into local minima. We also analyze the positioning performance of the uniform circular and cross-shaped electrodes arrays by using the subspace scanning algorithm combined with meta–EP PSO. According to the simulation, the calculation amount of the proposed algorithm is greatly reduced. Moreover, the positioning accuracy is effectively improved without changing the positioning accuracy and search speed.

New Three-dimensional Assessment Model and Optimization of Acoustic Positioning System

This paper addresses the problem of assessing and optimizing the acoustic positioning system for underwater target localization with range measurement. We present a new three-dimensional assessment model to evaluate the o... | Find, read and cite all the research you need on Tech Science Press

Robust Cooperative Moving Path Following Control for Marine Robotic Vehicles.

This paper presents results on recent developments pertaining to the coordinated motion control of a fleet of marine robotic vehicles. Specifically, we address the Cooperative Moving Path Following (CMPF) motion control problem, that consists of steering the robotic vehicles along a priori specified geometric paths that jointly move according to a target frame, while achieving a pre-defined coordination objective. To this end, each vehicle will need to communicate with their neighbors in order to cooperatively solve the CMPF task. Two distinct robust Moving Path Following motion control strategies for achieving robustness on the moving path following tasks are proposed. Experimental results demonstrating the application of CMPF to marine vehicles in the context of source localization and tracking of underwater targets are presented backed with stability and convergence guarantees.

Self-Contained High-SNR Underwater Acoustic Signal Acquisition Node and Synchronization Sampling Method for Multiple Distributed Nodes.

Aiming at the application demand in underwater noise monitoring, observation of marine animal, antisubmarine and underwater target localization, a high-SNR underwater acoustic signal acquisition (UASA) node that combines a self-contained acquisition system and floating platform is designed to improve the acquisition performance of a single UASA node, and a high-accuracy synchronization sampling method among multiple distributed UASA nodes based on master-slave dual phase-locked loops (MSDPLL) is proposed to improve the synchronization sampling accuracy. According to the equivalent model of hydrophone and application requirements, low noise signal conditioning circuit and large-capacity data storage modules are designed. Based on the long-term monitoring requirements for underwater acoustic signal and distributed positioning requirements for underwater targets, the structure of a single UASA node is designed and MSDPLL is developed for high-accuracy synchronization sampling among multiple UASA nodes. Related experimental results verified the performance of the UASA node and the synchronization sampling method.

Asynchronous Localization of Underwater Target Using Consensus-Based Unscented Kalman Filtering

Most applications of underwater acoustic sensor networks (UASNs) rely on accurate location information of targets. However, the asynchronous clock, stratification effect, and strong-noise characteristics of underwater environment make target localization more challenging as compared with terrestrial sensor networks. This paper focuses on an asynchronous localization issue for underwater targets, subjected to the isogradient sound speed and noise measurements. A network architecture including surface buoys, sensors, and the target is first designed, where the clocks on sensors and the target are not required to be synchronized. To eliminate the effect of asynchronous clocks, we establish the relationship between the propagation delay and the position. Particularly, the ray tracing approach is adopted to model the stratification effect. Then, a localization optimization problem is formulated to minimize the sum of all measurement errors. To solve the localization optimization problem, a consensus-based unscented Kalman filtering (UKF) localization algorithm is proposed, where the convergence conditions and Cramér-Rao lower bounds are also given. Finally, simulation results reveal that the proposed localization approach can reduce the localization time by comparing with the exhaustive search method. Meanwhile, the consensus-based UKF localization algorithm can improve localization accuracy as compared with other works.

Underwater Target Localization and Synchronization for a Distributed SIMO Sonar with an Isogradient SSP and Uncertainties in Receiver Locations

A distributed single-input multiple-output (SIMO) sonar system is composed of a sound source and multiple underwater receivers. It provides an important framework for underwater target localization. However, underwater hostile environments bring more challenges for underwater target localization than terrestrial target localization, such as the difficulties of synchronizing all the underwater receiver clocks, the varying underwater sound speed and the uncertainties of the locations of the underwater receivers. In this paper, we take the sound speed variation, the time synchronization and the uncertainties of the receiver locations into account, and propose the underwater target localization and synchronization (UTLS) algorithm for the distributed SIMO sonar system. In the distributed SIMO sonar system, the receivers are organized in a star topology, where the information fusion is carried out in the central receiver (CR). All the receivers are not synchronized and their positions are known with uncertainties. Moreover, the underwater sound speed is approximately modeled by a depth-dependent sound speed profile (SSP). We evaluate our proposed UTLS algorithm by comparing it with several benchmark algorithms via numerical simulations. The simulation results reveal the superiority of our proposed UTLS algorithm.

Optimal path shape for range-only underwater target localization using a Wave Glider

Underwater localization using acoustic signals is one of the main components in a navigation system for an autonomous underwater vehicle (AUV) as a more accurate alternative to dead-reckoning techniques. Although different methods based on the idea of multiple beacons have been studied, other approaches use only one beacon, which reduces the system’s costs and deployment complexity. The inverse approach for single-beacon navigation is to use this method for target localization by an underwater or surface vehicle. In this paper, a method of range-only target localization using a Wave Glider is presented, for which simulations and sea tests have been conducted to determine optimal parameters to minimize acoustic energy use and search time, and to maximize location accuracy and precision. Finally, a field mission is presented, where a Benthic Rover (an autonomous seafloor vehicle) is localized and tracked using minimal human intervention. This mission shows, as an example, the power of using autonomous vehicles in collaboration for oceanographic research.

DOA Estimation for Underwater Wideband Weak Targets Based on Coherent Signal Subspace and Compressed Sensing.

Direction of arrival (DOA) estimation is the basis for underwater target localization and tracking using towed line array sonar devices. A method of DOA estimation for underwater wideband weak targets based on coherent signal subspace (CSS) processing and compressed sensing (CS) theory is proposed. Under the CSS processing framework, wideband frequency focusing is accompanied by a two-sided correlation transformation, allowing the DOA of underwater wideband targets to be estimated based on the spatial sparsity of the targets and the compressed sensing reconstruction algorithm. Through analysis and processing of simulation data and marine trial data, it is shown that this method can accomplish the DOA estimation of underwater wideband weak targets. Results also show that this method can considerably improve the spatial spectrum of weak target signals, enhancing the ability to detect them. It can solve the problems of low directional resolution and unreliable weak-target detection in traditional beamforming technology. Compared with the conventional minimum variance distortionless response beamformers (MVDR), this method has many advantages, such as higher directional resolution, wider detection range, fewer required snapshots and more accurate detection for weak targets.

Target Localization for a Distributed SIMO Sonar With an Isogradient Sound Speed Profile

A distributed single-input multiple-output (SIMO) sonar system makes use of a sound source and a distributed star receiver network to localize targets. Compared with the terrestrial target localization, there are more challenges for underwater target localization. The underwater sound speed varies with depth, temperature, and salinity. As a result, the propagation path of the acoustic signal is not a straight line. It makes existing straight-line based distance measurements less accurate. Furthermore, time synchronization, which is closely related to time-based localization, has to be carried out because of the absence of GPS and clock differences of underwater devices. In this paper, we take the sound speed variation and time synchronization into account and propose two underwater target localization algorithms, namely, the space-alternating generalized expectation maximization-based underwater target localization (SAGE-UTL) and the nonlinear weighted least squares based underwater target localization (NWLS-UTL), for the distributed SIMO sonar system. The SAGE-UTL algorithm is designed for the situation, where the central receiver of the star receiver network needs to remain silent for its own safety. On the other hand, the NWLS-UTL algorithm is designed for the other situation, where the silence of the central receiver is not required. We assume that all the receivers are not synchronized, and the speed variation can be approximately modeled by a depth-dependent sound speed profile. Our proposed algorithms can jointly achieve target localization and time synchronization. We evaluate the SAGE-UTL and the NWLS-UTL algorithms with several numerical simulations. The results show good performance of our proposed algorithms compared with the Cramer–Rao bound and the tailored benchmark algorithms, such as the approximate nonlinear least squares algorithm and the approximate space-alternating generalized expectation maximization based underwater target localization algorithm.

Optimal multiple underwater target localization and tracking using two surface acoustic ranging sensors

In many scientific and commercial missions at sea, it is of crucial importance to localize one ore more targets underwater. This objective meets with difficulties due to the unavailability of GPS underwater and the high cost of the equipment classically used for target localization. For these reasons, there has been a surge of interest in the problem of range-based underwater target localization, defined as that of localizing a group of unknown (fixed/moving) targets resorting to surface vehicles (called trackers) equipped with sensors capable of measuring their distances to the targets. In this setup, the surface sensor nodes should be placed according to some optimality criterion aimed at maximizing the information available for target tracking. In addition, the number of sensor nodes should be kept to a minimum in order to avoid the use of a complex and expensive network of vehicles that must be positioned and controlled in a coordinated manner. Motivated by these considerations, in this paper we study the problem of multiple target localization using two trackers and present a constructive method to generate a family of optimal waypoints for the trackers. The use of two surface sensors is motivated by the fact that a single surface sensor does not provide enough positioning accuracy for multiple target localization simultaneously. For two and three targets, we provide a family of analytical solutions for optimal sensor node placements. Further, the proposed solutions can be extended to more than three targets under some well-defined constraints on the target configuration. The optimal sensor positions are derived by maximizing the determinants of appropriately defined Fisher information matrices associated with each of the targets. It is shown that the optimal sensor configuration thus obtained lends itself to an interesting and useful geometrical interpretation. Simulation examples illustrate the results derived.

Range-based cooperative underwater target localization

The paper addresses the problem of range-based cooperative underwater target localization. In its simplest form, target localization aims to estimate the position of a stationary or mobile target by using range measurements between the target and a vehicle, called a tracker, undergoing a trajectory that can be measured on-line. In this context, the tracker must execute sufficiently exciting maneuvers so as to maximize the range-based information available for target localization. The paper extends this set-up to the case where the tracker works in cooperation with another vehicle, called companion, that can also measure ranges to the target and shares this info with the tracker. The latter may have access to the position of the companion or, in some cases, only to the range between the two vehicles. We consider three different operating scenarios where the motion of the tracker is chosen so as to increase the accuracy with which the position of the target can be estimated. The scenarios reflect the situations where the motion of the companion vehicle satisfies one of three conditions: i) the motion is not defined a priori and can also be optimized, ii) the motion is fixed a priori and is known to the tracker (scenario in which the tracker benefits from the extra information acquired by the companion vehicle, which tracks a desired trajectory in the context of a separate, independent mission), and iii) the motion is not known a priori and must be learned in the course of the mission. By adopting an estimation-theoretical settings, optimal trajectories are computed by maximizing the determinant of an appropriately defined Fisher information matrix (FIM), subjected to vehicle maneuvering constraints and inter-vehicle collision avoidance. Simulation results illustrate the methodology adopted for cooperative target localization.

Adaptive Matched Field Processing for Source Localization Using Improved Diagonal Loading Algorithm

Matched field processing (MFP) has been a method widely applied for shallow underwater target localization, which is a critical issue in underwater acoustic. To enhance the efficiency of conventional MFP methods, different adaptive MFP algorithms have been developed; the white noise constraints (WNC) MFP or diagonal loading (DL) algorithm is such a typical one. The WNC or DL one has been considered to be the most desirable method because it is more robust to environment mismatch in practical in comparison with the minimum-variance distortionless response MFP algorithm, a popular high-resolution method. Although having exceptional ability to localize underwater sources in mismatch scenarios, the DL method has still been not reach high resolution in certain cases. In the paper, we proposed an adaptive method known as improved diagonal loading algorithm to make an increase in the resolution and the peak background rate in the ambiguity surface of source localization results in comparison with DL one. The proposed algorithm works by adding one more parameter that is adjusted in the steering vector of the DL algorithm. The simulation results show that the new algorithm attains better beamforming performance in terms of high resolution than the existing adaptive MFP algorithms in the case of environmental mismatch caused by noise effects and the limitation of the snapshots.

Optimal Sensor Placement for Acoustic Underwater Target Positioning With Range-Only Measurements

This paper addresses the problem of optimal acoustic sensor placement for underwater target localization in 3-D using range measurements only. By adopting an estimation theoretical framework, the optimal geometric sensor formation that will yield the best achievable performance in terms of target positioning accuracy is computed by maximizing the determinant of an appropriately defined Fisher information matrix (FIM). For mathematical tractability, it is assumed that the measurements of the ranges between the target and a set of acoustic sensors are corrupted with white Gaussian noise. For the sake of completeness, an explicit analytical result for a generic $n$ -sensor network is first obtained for the case when there is no uncertainty in the prior knowledge about the target position. The result is then extended to the practical case where the target is known to lie inside a region of uncertainty. The optimal sensor configuration thus obtained lends itself to an interesting and useful geometrical interpretation. In addition, the “spreading” of the configuration is shown to depend on the number of range measurements, target depth, and the probability distribution function that characterizes the prior knowledge about the target position. Results are also obtained for the problem of optimal sensor placement with constraints, namely, by considering that the sensors can be either located at the sea surface or distributed between the surface and the seabed. The connection between 2-D and 3-D scenarios is clarified. Simulation examples illustrate the key results derived.

Three-dimensional underwater target localization with circular vector sensor array in strong reverberation environment

As reverberation can be regarded as an output of time-varying stochastic filtering of the emitted signal, it always leads to high false alarm in shallow water. In this case, some methods have been used to suppress reverberation such as empirical mode decomposition filter, match filter, etc. However, a strong correlation between transmitted signal and reverberation restricts the performance of these methods. In this paper,a novel method based on a circular vector sensor array is proposed to detect and locate multiple targets, respectively, in a strong reverberation environment by using the difference of the Doppler shift distribution between reverberation and target echo. First, spherical harmonic decomposition and beamforming are used to process the wideband signal and generate multiple beams which contain spatial information of interested region. Then, fractional Fourier transform is adopted to get Doppler shift distribution and localization information of reverberation and target echo. Multiple targets can be detected and located separately by estimating variance fluctuation associated with the reflections in different beams. Simulation result shows that this method performs efficiently and reliably in server reverberation environment without any prior information.

Integrated Motion Planning, Control, and Estimation for Range-Based Marine Vehicle Positioning and Target Localization

Abstract: The paper addresses the problems of range-based marine vehicle positioning and target localization. Vehicle positioning aims to estimate the positions of one or more vehicles from a sequence of range measurements to fixed or moving acoustic beacons with known locations. In this context, the vehicles must execute sufficiently exciting maneuvers so as to maximize the range-based information available for multiple vehicle positioning. Using an estimation theoretical setting, the vehicle trajectories are computed by maximizing the determinant of a suitably defined Fisher information matrix (FIM), subject to inter-vehicle collision avoidance and vehicle maneuvering constraints. A numerical solution is proposed for the general case. Analytical solutions are obtained in the case of one vehicle and one beacon, when the latter undergoes trajectories that are straight lines, pieces of arcs, or a combination thereof. The theoretical analysis is complemented with practical experiments that focus on the dual problem of underwater target localization. The objective is to estimate the position of a moving underwater target by using range measurements between the target and a vehicle, called a tracker, undergoing a trajectory that can be measured on-line. The experimental set-up includes a surface and an autonomous underwater vehicle of the MEDUSA*-class playing the roles of tracker and target, respectively. In the methodology adopted for system implementation the tracker runs three key algorithms simultaneously, over a sliding time window: i) tracker motion planning, ii) tracker motion control, and iii) target motion estimation based on range data acquired on-line.

A real-time magnetic localization method of underwater non-cooperative magnetic targets based on unscented particle filter

A real-time magnetic localization method based on unscented particle filter (UPF) is proposed to solve the problem for real-time localization of underwater non-cooperative magnetic targets. The state space model of non-cooperative magnetic targets is set up according to its motion characteristic, and the state is estimated in real time by UPF. In order to improve the observability of the system, the particle state is constrained and magnetic moment is inverted by the least square method. The simulation results and ferromagnetic object localization experimental results show that the method is good in localization precision and real-time performance, which can be applied to the real-time magnetic localization in near field.

Design and Development of a Littoral AUV for Underwater Target Localization and Homing Using Vision and SONAR Module

This paper presents the design and development of a modular littoral autonomous underwater vehicle called “ZYRA” having six degrees of freedom for performing the following tasks underwater: target (sound sources emitting frequencies between 1 Hz and 180 KHz) localization and homing, buoy detection. The development of the AUV has been divided into, namely, five sections: mechanical design and fabrication, embedded and power systems, control and software, image processing, and underwater acoustics. A fully functional AUV has been tested in a self-created arena with different tasks spread out in a shallow water environment. Two different kinds of experimental results have been presented: first the experimental results of the SONAR module and second based on the number of successful outcomes per total number of trials for each task.

Research on Localization Principle and Method for Multistation Range-only Target Tracking System

Observable condition for multistation range-only system was analyzed according to the characteristics of underwater target localization in the conditions of network warfare. When the target is stationary or travels in straight-line movement, it is able to be observed by range-only system. The target localization parameters are estimated by least squares estimator algorithm, which has simple form and does not need initial values. Simulation results show that the algorithm has fast convergence speed, good stability and high accuracy.

Sensor-Target Geometry for Hybrid Bearing/Range Underwater Localization

In this paper, the influence of sensor-target relative geometry on the potential performance of underwater target localization with hybrid bearing/range sensors is investigated. The optimality criterion function is built on the knowledge of Fisher information matrix (FIM), and another analysis on the mean squared error (MSE) is also presented. For a fixed distance between the sensors to the underwater target, the MSE is minimized if and only if the determinant of the FIM is maximized. The main contribution in this paper is the dependence of the range measurement error on the acoustic propagation distance because of the complex underwater environment, which result in a different FIM expression compared to the ideal assumption case. Simulation results are provided to show the effectiveness of the algorithms presented.

DOA estimation based on fourth order cumulant beamforming for nonuniform linear array of DIFAR sonobuoys

The Directional Frequency Analysis and Recording (DIFAR) sonobuoy has been widely used in underwater target localization because it can capture more information than the Low Frequency Analysis and Recording (LOFAR) omnidirectional sonobuoy. Recently, array processing for fields of DIFAR sonobuoys has attracted considerable attention in order to enhance the direction of arrival (DOA) estimation performance and accuracy. DIFAR sonobuoys may become irregularly spaced due to the deployment method and the drift experienced once deployed, resulting in a nonuniform array. In this paper, we demonstrate the fourth-order cumulant beamforming (FOC-BF) technique to estimate the DOA for a nonuniform linear array of DIFAR sonobuoys. FOC-BF was compared with the conventional beamforming (CBF) through simulation works. The results show that FOC-BF provides better spatial spectrum with lower sidelobes than CBF. Furthermore, FOC-BF provides superior DOA estimation accuracy over CBF at very low signal to noise ratios (SNR).