Ultra-short Baseline System Research Articles

Carrier Phase-Based Underwater Source Localization for Ultrashort Baseline

In this paper, we propose a phase-based pseudorange estimation and source localization algorithm to improve the localization performances of ultrashort baseline (USBL) systems. The conventional USBL system estimates pseudorange through cross-correlation of received chirps. However, due to the limited sampling rate, precise pseudorange cannot be estimated, resulting in low localization performance. The proposed method calculates the number of wavelengths between the transducer and receiver and detects the initial phase to estimate the pseudorange more accurately than the conventional method. It also improves localization performance by estimating and compensating for phase variations by underwater channels. The source localization performances of the proposed method and the conventional methods were compared and analyzed through computer simulations and ocean experiments, and the proposed method had better localization performances than the conventional methods.

Voronoi Diagram-based USBL Outlier Rejection for AUV Localization

USBL systems are essential for providing accurate positions of autonomous underwater vehicles (AUVs). On the other hand, the accuracy can be degraded by outliers because of the environmental conditions. A failure to address these outliers can significantly impact the reliability of underwater localization and navigation systems. This paper proposes a novel outlier rejection algorithm for AUV localization using Voronoi diagrams and query point calculation. The Voronoi diagram divides data space into Voronoi cells that center on ultra-short baseline (USBL) data, and the calculated query point determines if the corresponding USBL data is an inlier. This study conducted experiments acquiring GPS and USBL data simultaneously and optimized the algorithm empirically based on the acquired data. In addition, the proposed method was applied to a sensor fusion algorithm to verify its effectiveness, resulting in improved pose estimations. The proposed method can be applied to various sensor fusion algorithms as a preprocess and could be used for outlier rejection for other 2D-based location sensors.

An Underwater Source Localization Method Using Bearing Measurements.

Angle-of-arrival (AOA) measurements are often used in underwater acoustical localization. Different from the traditional AOA model based on azimuth and elevation measurements, the AOA model studied in this paper uses bearing measurements. It is also often used in the Ultra-Short Baseline system (USBL). However, traditional acoustical localization needs additional range information. If the range information is unavailable, the closed-form solution is difficult to obtain only with bearing measurements. Thus, a localization closed-form solution using only bearing measurements is explored in this article. A pseudo-linear measurement model between the source position and the bearing measurements is derived, and considering the nonlinear relationship of the parameters, a weighted least-squares optimization equation based on multiple constraints is established. Different from the traditional two-step least-squares method, the semidefinite programming (SDP) method is designed to obtain the initial solution, and then a bias compensation method is proposed to further minimize localization errors based on the SDP result. Numerical simulations show that the performance of the proposed method can achieve Cramer-Rao lower bound (CRLB) accuracy. The field test also proves that the proposed method can locate the source position without range measurements and obtain the highest positioning accuracy.

An evaluation research of constant false alarm rate algorithm for the application of underwater vehicles management system based on USBL sonar principles in shallow water

The paper presents an overview of underwater traffic management systems utilizing sonar principles. Based on the evaluation of the current situation both domestically and internationally, the research team has proposed the development of a underwater signal processing algorithm based on an adaptive threshold in the Ultra-short Baseline System (USBL). The theoretical results were implemented on FPGA hardware, not only enhancing signal detection capabilities but also meeting real-time signal processing requirements when deployed in complex underwater conditions in various shallow water regions of Vietnam. The research's future direction indicates substantial potential in the practical application of hydroacoustic signal processing algorithms when executing hardware implementations.

Experimental Analysis of Deep-Sea AUV Based on Multi-Sensor Integrated Navigation and Positioning

The operation of underwater vehicles in deep waters is a very challenging task. The use of AUVs (Autonomous Underwater Vehicles) is the preferred option for underwater exploration activities. They can be autonomously navigated and controlled in real time underwater, which is only possible with precise spatio-temporal information. Navigation and positioning systems based on LBL (Long-Baseline) or USBL (Ultra-Short-Baseline) systems have their own characteristics, so the choice of system is based on the specific application scenario. However, comparative experiments on AUV navigation and positioning under both systems are rarely conducted, especially in the deep sea. This study describes navigation and positioning experiments on AUVs in deep-sea scenarios and compares the accuracy of the USBL and LBL/SINS (Strap-Down Inertial Navigation System)/DVL (Doppler Velocity Log) modes. In practice, the accuracy of the USBL positioning mode is higher when the AUV is within a 60° observation range below the ship; when the AUV is far away from the ship, the positioning accuracy decreases with increasing range and observation angle, i.e., the positioning error reaches 80 m at 4000 m depth. The navigational accuracy inside and outside the datum array is high when using the LBL/SINS/DVL mode; if the AUV is far from the datum array when climbing to the surface, the LBL cannot provide accurate position calibration while the DVL fails, resulting in large deviations in the SINS results. In summary, the use of multi-sensor combination navigation schemes is beneficial, and accurate position information acquisition should be based on the demand and cost, while other factors should also be comprehensively considered; this paper proposes the use of the LBL/SINS/DVL system scheme.

Research on developing an adaptive algorithm for enhancing the quality of underwater positioning based on the sonar USBL principle

The paper proposes an enhanced solution for improving the accuracy of underwater object positioning based on the Ultra-Short Baseline (USBL) sonar principle. In shallow water regions, complex hydrological phenomena affect the quality of underwater acoustic signal transmission and reception, making it essential to enhance the processing of these signal groups. Through the USBL system model, the paper presents a model capable of adaptively selecting accurate signals amidst the noisy underwater environment. The proposed model is implemented and validated in practice using FPGA hardware in Lan Ha Bay. The results demonstrate the effectiveness of the proposed algorithm compared to conventional approaches, as it extends the management range and optimizes the transmission power of the system, even in cases of low signal-to-noise ratio.

An invariant error-based SINS/DVL/USBL tightly coupled integrated navigation algorithm and its robust state estimator

The existing strapdown inertial navigation system (SINS)/Doppler velocity log (DVL)/ultra-short baseline system (USBL) integrated navigation error models directly apply algebraic differences to define the vector error, which is not strictly accurate. Considering that the invariant error definitions derived from Lie group theory have been used in the navigation field to obtain more accurate linear error models, in this paper, a new SINS/DVL/USBL integrated navigation system is investigated based on the invariant error definition and tightly coupled structure. In order to suppress the effect of measurement outliers on navigation accuracy, a new statistical similarity measure (SSM)-based multiple adaptive outlier-robust state estimator (MAORSE) is proposed. It decomposes the noise covariance matrix into multiple sub-matrices. Through the estimation and adjustment of sub-matrices, the influence of abnormal observations on the filtering results is weakened while realizing the full utilization of normal observation information. The test results demonstrate the effectiveness and superiority of the proposed invariant error-based SINS/DVL/USBL tightly coupled integrated navigation algorithm and SSM-based MAORSE.

A novel INS/USBL/DVL integrated navigation scheme against complex underwater environment

In view of challenges of complex underwater environments with a high occurrence of sensor outliers, traditional Kalman filter (KF)-based localization methods are difficult to achieve precise positioning. To address this issue, a factor graph optimization (FGO)-based tightly-coupled (TC) inertial navigation system (INS)/ultra-short baseline system (USBL)/Doppler velocity log (DVL) scheme and core fusion algorithm are proposed. The FGO method is used to construct a TC INS/USBL/DVL factor graph model, and a weight function is added to adjust the weights of each factor, thereby improving the utilization of underwater sensor information and enhancing the accuracy and reliability of underwater navigation. The feasibility of the proposed scheme is verified through simulations and field tests. The results show that the proposed method outperforms KF-loosely-coupled (KF-LC), KF-TC, and FGO-LC methods, with horizontal position accuracy improvements of 29.2%, 6.6%, and 13.2%, respectively. Moreover, the proposed method exhibits smooth navigation error performance in the presence of abnormal sensor information.

An Installation Angle Error Calibration Method in an Ultra-Short Baseline System Based on a Dual Transponder

Abstract The installation error of an acoustic transceiver array is one of the important error sources in an ultra-short baseline (USBL) system. In a USBL system with a positioning accuracy of 0.5%, an installation error angle of 1° will lead to a positioning error of 1.7% times the slant distance. In this paper, a dual transponder-based installation angle error calibration method for USBL is proposed. First, the positioning errors induced by various installation angles are deduced and analysed using the linear measurement of seafloor targets. Then, an iterative algorithm is proposed that estimates the rolling alignment error, pitching alignment error, and heading alignment error, in that order. The simulation and experienced results show that, after three iterations, the estimates of the three alignment errors can converge quickly, all of the estimates converge to within 0.001° and the estimated values are very close to the true values. The horizontal positioning error caused by the installation error angle can be reduced by nearly 75%. The method has good effectiveness and robustness, and can greatly improve the positioning accuracy of the USBL system.

Ultra-short baseline positioning delay estimation based on signal preprocessing and fourth-order cumulant

To address the problem that the traditional generalized cross correlation (GCC) method in ultra-short baseline (USBL) positioning systems has a poor delay estimation accuracy in a low signal-to-noise ratio environment or complex noise background, a generalized quadratic cross correlation (GQCC) time delay estimation algorithm based on signal preprocessing and fourth-order cumulants is proposed. The noisy signal was first preprocessed using singular value decomposition and wavelet denoising. Then, the delay was calculated using an algorithm that combined the GQCC and the fourth-order cumulant. The results of the simulation and sea trial demonstrate that the proposed method is superior to the GCC method and the GQCC method and may significantly increase the positioning accuracy of the USBL system. This technique can offer a fresh technological perspective for weak signal detection and passive positioning of small targets in ocean detection.

A Robust INS/USBL/DVL Integrated Navigation Algorithm Using Graph Optimization

The Autonomous Underwater Vehicle (AUV) is usually equipped with multiple sensors, such as an inertial navigation system (INS), ultra-short baseline system (USBL), and Doppler velocity log (DVL), to achieve autonomous navigation. Multi-source information fusion is the key to realizing high-precision underwater navigation and positioning. To solve the problem, a fusion scheme based on factor graph optimization (FGO) is proposed. Due to multiple iterations and joint optimization of historical data, FGO could usually show a better performance than the traditional Kalman filter. In addition, considering that USBL and DVL are usually heavily influenced by the environment, outliers are often present. A robust integrated navigation algorithm based on a maximum correntropy criterion and FGO scheme is proposed. The proposed algorithm solves the problem of multi-sensor fusion and non-Gaussian noise. Numerical simulations and field tests demonstrate that the proposed FGO scheme shows a better performance and robustness than the traditional Kalman filter. Compared with the traditional Kalman filtering, the positioning accuracy is improved by 5.3%, 9.1%, and 5.1% in the east, north, and height directions. It can realize a more accurate navigation and positioning of underwater multi-sensors.

A Novel INS/USBL Integrated Navigation Scheme via Factor Graph Optimization

Factor graph optimization (FGO) is a well-known approach in the robotics field. Due to multiple iterations and application of large amounts of data, it usually could superior performance than the Kalman Filter (KF) under complex scenarios. However, it is rarely used in the underwater environment, especially for applications based on fiber-optic inertial navigation. Taking the ultra-short baseline system (USBL) as the application background, a novel inertial navigation system (INS)/USBL integrated navigation scheme based on FGO is presented in this paper. The traditional pre-integration factor simplifies the earth rotation and coordinate system, which limits its application in high-precision sensors. This paper proposed an improved pre-integration model using the high precision measurements of fiber optics gyroscope in FGO. Simulation and field tests proved that, with the FGO method, improved accuracy of INS/USBL integration was obtained compared to the traditional KF method. It confirms the potential of FGO in the applications of underwater navigation and positioning.

Passive Inverted Ultra-Short Baseline Positioning for a Disc-Shaped Autonomous Underwater Vehicle: Design and Field Experiments

Underwater positioning is critical to autonomous underwater vehicles (AUVs) for navigation and geo-referencing. The rapid attenuation of the electromagnetic wave in the underwater environment prevents the use of traditional positioning methods such as the Global Positioning System, whereupon acoustic methods like ultra-short baseline (USBL) positioning systems play an important role in AUV navigation. However, the high cost and complexity of classical USBL systems have stifled the democratization of these technologies, which leads to a new method called passive inverted ultra-short baseline (piUSBL) positioning. In a typical piUSBL system, a single beacon is placed at a reference point, periodically broadcasting a positioning signal. A passive USBL receiver, time-synchronized to the beacon, is mounted on an AUV to get one-way travel-time (OWTT) slant range and azimuth estimates. The passive nature of the receiver means the system is inexpensive, low-power, and lightweight. Particularly, the omnidirectional broadcasted signals offer a feasible solution for concurrent multi-AUV navigation. This letter demonstrates a full-stack design and development of a piUSBL positioning system, and presents evaluations of the accuracy and reliability of the system through a series of experiments. More significantly, a successful sea trial of a disc-shaped AUV outfitted with our piUSBL was conducted in the South China Sea.

An USBL/DR Integrated Underwater Localization Algorithm Considering Variations of Measurement Noise Covariance

Ultrashort baseline (USBL) positioning system is an important part of the integrated navigation for underwater vehicles. The single USBL positioning system has problems such as reduced accuracy of azimuth measurement due to target motion and large impact of small angular variations, especially in the region where the target is close to the conical boundary, that is, the low-elevation region. To improve the positioning accuracy of the USBL-based integrated navigation system, a tightly coupled USBL/Dead Reckoning (DR) integrated localization algorithm that considers the time varying characteristics of the measurement noise was proposed, and the filtering model of the algorithm was designed. The algorithm exploits the mechanism of the azimuth measurement covariance variation of the USBL system, constructs an adaptive measurement noise estimator for the USBL system, and applies it to the integration filtering of USBL/DR data. A nonlinear extended Kalman filtering (EKF) model was used to fuse the USBL positioning and dead reckoning trajectories. A number of simulation tests with different elevation angle settings were performed to compare the performance of the proposed algorithm with that of a conventional EKF for underwater localization. The test results reveal that the proposed algorithm can effectively reduce the positioning error caused by the change in the relative azimuth of the acoustic signal owing the motion of the mother ship and the motion of the underwater vehicle.

The Fine Calibration of the Ultra-Short Baseline System With Inaccurate Measurement Noise Covariance Matrix

The Fine Calibration of the Ultra-Short Baseline System With Inaccurate Measurement Noise Covariance Matrix

Efficient Underwater Acoustical Localization Method Based On Time Difference and Bearing Measurements

This article addresses the underwater acoustical localization problem by using the time-difference-of-arrival (TDOA) and bearing-angle-of-arrival (BAOA) measurements. For the underwater acoustic equipment, such as the ultrashort baseline system (USBL), whose bearing measurements are different from the traditional angle-of-arrival (AOA) model, a closed-form solution for the hybrid TDOA/BAOA-based source localization problem is developed. However, the solution suffers from the measurement noise and cannot achieve the Cramer–Rao lower bound (CRLB) performance in the case of large measurement noise. Thus, an iterative constrained weighted least-squares method is presented to further minimize the error in the case of large noise. The CRLB for hybrid TDOA/BAOA source localization is analyzed, and the solution is proved to achieve the CRLB performance. Numerical simulations and field tests demonstrate that the proposed method outperforms the traditional methods in terms of estimation bias and accuracy. It can achieve the CRLB performance better.

A Calibration Method of USBL Installation Error Based on Attitude Determination

The Ultra-short baseline (USBL) positioning system has important application in the positioning of underwater vehicles. The installation error angle of the USBL positioning system has an important influence on the positioning accuracy of USBL system. The traditional calibration methods have limited estimation accuracy for installation error angles and have high route requirements. To solve the above problems, a calibration method of installation error angle based on attitude determination is proposed in this paper. When strapdown inertial navigation system (SINS) and USBL are fixed together in the application process, the installation error angle of USBL is fixed and unchanged. Then the calibration of installation error angle can be accomplished with the idea of attitude determination. The vector observation model based on the installation error angle matrix is established first. Observation vectors are obtained by the relative position of transponders in the USBL coordinate frame. The reference vector is calculated by position of transponder, position and attitude of SINS and lever arm between SINS and USBL. By constructing the observation vectors and the reference vectors, the proposed method can calibrate the installation error angle of SINS and USBL in real time. The advantages of the proposed method are that it has no specific requirements for the calibration route and can calibrate the installation error angle in real time with high accuracy. In order to verify the performance of the proposed algorithm, simulation experiment and field experiment are carried out in this paper. The results of simulation experiment and field experiment show that the proposed method can give the estimated installation error angle of USBL in real time, and the estimated result is the best among several methods. The proposed method can not only achieve the calibration of the installation error angle in circular trajectory, but also in straight trajectory.

A calibration method of ultra-short baseline installation error with large misalignment based on variational Bayesian unscented Kalman filter.

The ultrashort baseline system is widely used in ships and underwater navigation and positioning. The misalignment and level arm with the inertial measurement unit are the two sources of positioning inaccuracy. The accuracy of calibration is usually affected by measurement noise and linearization of the observation equation. In order to improve the calibration accuracy, the variational Bayesian unscented Kalman filter (VBUKF) method is proposed for the calibration of the ultrashort baseline installation error in the paper. The detailed derivation of VBUKF for the calibration is presented in the paper. Simulation experiments and field experiments were carried out, respectively, to verify the algorithm. The simulation results show that the proposed method can calibrate the installation error of the sensors in real time on line. The field experiment verified that the algorithm improves the calibration accuracy of the installation error under the large misalignment. The positioning accuracy is also improved compared with the traditional method.

Inverted ultra-short baseline signal design for multi-AUV navigation

Recent years scholars have seen remarkable advancements in Autonomous Underwater Vehicle (AUV) technologies despite limited underwater energy. Multi-AUV positioning technology is an especially popular collaborative research subject; at present, long baseline and ultra-short baseline systems are available for multi-AUV positioning. Long baseline positioning has many disadvantages including overly complex settings and limited effective area for beacon collection.Ultra-short baseline positioning system is rather heavy and allows for fewer users.This paper proposes a new model based on the inverted ultra-short baseline (iUSBL) for AUV positioning. The model accommodates many users, maintains secret positions under deep sea conditions, and functions over lengthy distances, among other advantages. Highly detectable signals are designed for enhanced positioning accuracy in the proposed system. Simulation and anechoic tank experiment results indicate that the direct sequence spread spectrum (DSSS) signal is the optimal transmission signal during the positioning process.

Angular misalignment calibration method for ultra‐short baseline positioning system based on matrix decomposition

For an ultra-short baseline (USBL) positioning system, the angular misalignment between the acoustic array and attitude sensor will introduce overwhelming positioning errors. In order to eliminate this type of errors, a method to calibrate angular misalignment is proposed here. In the method, individual angular misalignment is estimated through the decomposition of the related rotating matrix and overall angular misalignment is calculated using an iterative estimator. Not only does the method determine the angular misalignment more accurately but also it can be applicable to any arbitrary trajectory even the pre-determined trajectory is distorted by the environmental forces (such as winds, currents). The estimation error of the method is analysed through a simulation with different types of trajectories. Its performance is also evaluated in a field experiment. The method is compared with an existing method using both simulated and field data. The simulation and field experiment results indicate that the method has better performance and does improve the positioning accuracy of a USBL system.