Simulation of an Inertial Acoustic Navigation System With Range Aiding for an Autonomous Underwater Vehicle

This paper presents an integrated navigation system for underwater vehicles to improve the performance of a conventional inertial acoustic navigation system by introducing range measurement. The integrated navigation system is based on a strapdown inertial navigation system (SDINS) accompanying range sensor, Doppler velocity log (DVL), magnetic compass, and depth sensor. Two measurement models of the range sensor are derived and augmented to the inertial acoustic navigation system, respectively. A multirate extended Kalman filter (EKF) is adopted to propagate the error covariance with the inertial sensors, where the filter updates the measurement errors and the error covariance and corrects the system states when the external measurements are available. This paper demonstrates the improvement on the robustness and convergence of the integrated navigation system with range aiding (RA). This paper used experimental data obtained from a rotating arm test with a fish model to simulate the navigational performance. Strong points of the navigation system are the elimination of initial position errors and the robustness on the dropout of acoustic signals. The convergence speed and conditions of the initial error removal are examined with Monte Carlo simulation. In addition, numerical simulations are conducted with the six-degrees-of-freedom (6-DOF) equations of motion of an autonomous underwater vehicle (AUV) in a boustrophedon survey mode to illustrate the effectiveness of the integrated navigation system.     

Visually Augmented Navigation for Autonomous Underwater Vehicles

As autonomous underwater vehicles (AUVs) are becoming routinely used in an exploratory context for ocean science, the goal of visually augmented navigation (VAN) is to improve the near-seafloor navigation precision of such vehicles without imposing the burden of having to deploy additional infrastructure. This is in contrast to traditional acoustic long baseline navigation techniques, which require the deployment, calibration, and eventual recovery of a transponder network. To achieve this goal, VAN is formulated within a vision-based simultaneous localization and mapping (SLAM) framework that exploits the systems-level complementary aspects of a camera and strap-down sensor suite. The result is an environmentally based navigation technique robust to the peculiarities of low-overlap underwater imagery. The method employs a view-based representation where camera-derived relative-pose measurements provide spatial constraints, which enforce trajectory consistency and also serve as a mechanism for loop closure, allowing for error growth to be independent of time for revisited imagery. This article outlines the multisensor VAN framework and demonstrates it to have compelling advantages over a purely vision-only approach by: 1) improving the robustness of low-overlap underwater image registration; 2) setting the free gauge scale; and 3) allowing for a disconnected camera-constraint topology.      

Survey of underwater robot positioning navigation

Underwater robot positioning and navigation achieve autonomous underwater robot movement based on the premise that positioning obtains the coordinates of the relative position of the underwater robot using a sensor, and navigation yields a known location to the destination path planning. Due to the location of an underwater robot and the complex and changing environment in which it operates, it is difficult to achieve precise positioning using the traditional positioning method. This paper systematically analyzes and summarizes several typical localization and navigation methods of underwater robots, such as multisensor information fusion technology, underwater acoustic localization and navigation methods, GPS buoy, underwater vision, SLAM and coordinate localization and navigation of multiple underwater robots. Multisensory information fusion technology integrates the advantages of the above methods, enhances the system stability and robustness, overcomes the disadvantages of traditional positioning and navigation, and enables the autonomous navigation and positioning of underwater robots. Underwater acoustics enable flexible and convenient positioning, whereas GPS can achieve high-precision and high-positioning navigation information, and visual positioning effectively overcomes the problem of error accumulation. Multirobot cooperative positioning resolves the problem of positioning failure caused by the collapse of a single system and completes complex tasks that cannot be completed by a single robot, thus enhancing the stability and robustness of the system. This paper systematically describes the realization of these methods, presents an actual analysis of their respective advantages and problems, and discusses the development of the field of research prospects and application prospects.     

基于单水声信标距离量测的匹配定位方法

水声通信和测距能力是实现水下航行器准确定位的重要技术手段。当前基于水声定位的方法主要有利用测距和测向功能的水声定位技术以及水声测距辅助导航技术,二者的系统物理复杂度都比较高。本文提出了一种基于单水声信标距离量测的匹配定位方法,航行器在水声信标测距覆盖范围内,利用航行过程中多次测距信息构建测距圆序列形成位置约束,基于航位推算导航信息,将航行器在连续测距时间段内的相对航迹在圆序列上进行最优匹配,从而获得位置估计,通过对测距误差进行补偿可进一步提升定位精度。本方法所需物理系统结构复杂度低、可操作性强,仿真实验表明,该方法可以独立实现较高精度的定位。     

Deep Sea AUV Navigation Using Multiple Acoustic Beacons

Navigation is a critical requirement for the operation of Autonomous Underwater Vehicles (AUVs). To estimate the vehicle position, we present an algorithm using an extended Kalman filter (EKF) to integrate dead-reckoning position with acoustic ranges from multiple beacons pre-deployed in the operating environment. Owing to high latency, variable sound speed multipath transmissions and unreliability in acoustic measurements, outlier recognition techniques are proposed as well. The navigation algorithm has been tested by the recorded data of deep sea AUV during field operations in a variety of environments. Our results show the improved performance over prior techniques based on position computation.     

A Portable Matched-Field Processing System Using Passive Acoustic Time Synchronization

A portable matched-field processing (MFP) system for tracking marine mammals is presented, constructed by attaching a set of autonomous flash-memory acoustic recorders to a rope to form a four-element vertical array, or "insta-array." The acoustic data are initially time-synchronized by performing a matched-field global inversion using acoustic data from an opportunistic source, and then by exploiting the spatial coherence of the ocean ambient noise background to measure and correct for the relative clock drift between the autonomous recorders. The technique is illustrated by using humpback whale song collected off the eastern Australian coast to synchronize the array, which is then used to track the dive profile of the whale using MFP methods. The ability to deploy autonomous instruments into arbitrary "insta-array" geometries with conventional fishing gear may permit nonintrusive array measurements in regions currently too isolated, expensive, or environmentally hostile for standard acoustic equipment     

Underwater acoustic networks

With the advances in acoustic modem technology that enabled high-rate reliable communications, current research focuses on communication between various remote instruments within a network environment. Underwater acoustic (UWA) networks are generally formed by acoustically connected ocean-bottom sensors, autonomous underwater vehicles, and a surface station, which provides a link to an on-shore control center. While many applications require long-term monitoring of the deployment area, the battery-powered network nodes limit the lifetime of UWA networks. In addition, shallow-water acoustic channel characteristics, such as low available bandwidth, highly varying multipath, and large propagation delays, restrict the efficiency of UWA networks. Within such an environment, designing an UWA network that maximizes throughput and reliability while minimizing the power consumption becomes a very difficult task. The goal of this paper is to survey the existing network technology and its applicability to underwater acoustic channels. In addition, we present a shallow-water acoustic network example and outline some future research directions     

Estimation of Rapidly Time-Varying Sparse Channels

The estimation of sparse shallow-water acoustic communication channels and the impact of estimation performance on the equalization of phase coherent communication signals are investigated. Given sufficiently wide transmission bandwidth, the impulse response of the shallow-water acoustic channel is often sparse as the multipath arrivals become resolvable. In the presence of significant surface waves, the multipath arrivals associated with surface scattering fluctuate rapidly over time, in the sense that the complex gain, the arrival time, and the Dopplers of each arrival all change dynamically. A sparse channel estimation technique is developed based on the delay-Doppler-spread function representation of the channel. The delay-Doppler-spread function may be considered as a first-order approximation to the rapidly time-varying channel in which each channel component is associated with Doppler shifts that are assumed constant over an averaging interval. The sparse structure of the delay-Doppler-spread function is then exploited by sequentially choosing the dominant components that minimize a least squares error. The advantage of this approach is that it captures both the channel structure as well as its dynamics without the need of explicit dynamic channel modeling. As the symbols are populated with the sample Dopplers, the increase in complexity depends on the channel Doppler spread and can be significant for a severely Doppler-spread channel. Comparison is made between nonsparse recursive least squares (RLS) channel estimation, sparse channel impulse response estimation, and estimation using the proposed approach. The results are demonstrated using experimental data. In training mode, the proposed approach shows a 3-dB reduction in signal prediction error. In decision-directed mode, it improves significantly the robustness of the performance of the channel-estimate-based equalizer against rapid channel fluctuations.     

Spatial diversity equalization applied to underwater communications

Underwater acoustic digital communication is difficult because of the nature of the fading multipath channels. Digital signal processing, such as adaptive equalization, is known to greatly improve the communication data rate by limiting intersymbol interference (ISI). However, existing underwater acoustic equalization studies are limited to single-channel techniques, and spatial diversity processing is limited to selection or combining. In this paper, we design minimum mean-square error (MMSE) equalizers jointly among all spatial diversity channels. We call this spatial diversity equalization (SDE). Results are based on a very sparse vertical array in a midrange underwater acoustic channel. We study the effect of element number and placement, the length of the equalization filters, and linear feedforward versus nonlinear decision feedback algorithms. A suboptimum equalizer combiner (EC) is studied to alleviate the computational intensity of JCE. We first design the system for a known acoustic channel; later, some results are verified using adaptive algorithms. Results are presented both in terms of the mean-square error (MSE) and the probability of a symbol error. The latter is important as it is the ultimate interest for a digital communication system. We found that system performance improves rapidly with an increase in the number of spatial channels     

A Novel Method for Real-Time Monitoring of Channel Siltation Based on Bistatic Scattering Theory

Monitoring the thickness changes of channel siltation is paramount in safeguarding navigation and guiding dredging.This paper presents a novel method for realizing the field monitoring of channel siltation in real time.The method is based on the bistatic scattering theory and concerned more with the receiving and processing of multipath signal at high-frequency and small grazing angle.By use of the multipath propagation structure of underwater acoustic channel,the method obtains the silt thickness by calculating the relative time delay of acoustic signals between the direct and the shortest bottom reflected paths.Bistatic transducer pairs are employed to transmit and receive the acoustic signals,and the GPS time synchronization technology is introduced to synchronize the transmitter and receiver.The WRELAX (Weighted Fourier transform and RELAX) algorithm is used to obtain the high resolution estimation of multipath time delay.To examine the feasibility of the presented method and the accuracy and precision of the developed system,a series of sea trials are conducted in the southwest coast area of Dalian City,north of the Yellow Sea.The experimental results are compared with that using high-resolution dual echo sounder HydroBoxTM,and the uncertainty is smaller than ±0.06 m.Compared with the existing means for measuring the silt thickness,the present method is innovative,and the system is stable,efficient and provides a better real-time performance.It especially suits monitoring the narrow channel with rapid changes of siltation.     

Pseudo long base line navigation algorithm for underwater vehicles with inertial sensors and two acoustic range measurements

This paper presents an integrated navigational algorithm for unmanned underwater vehicles (UUV) using two acoustic range transducers and strap-down inertial measurement unit (SD-IMU). A range measurement model is derived for a UUV having one acoustic transducer and cruising around two reference transponders at sea floor or surface. The proposed algorithm, called pseudo long base line (PLBL), estimates the position of the vehicle integrating the SD-IMU signals corrected with the two range measurements. Extended Kalman filter was applied to propagate error covariance, to update measurement errors and to correct state equation whenever the external measurements are available. Simulations were conducted to illustrate the effectiveness of the PLBL using the 6-d.o.f. nonlinear numerical model of a UUV at current flow, excluding bottom-fixed DVL. This paper also shows the error convergence of the vehicle's initial position by the additional range measurements without velocity information.     

Analysis of a possible sea floor strain measurement system

Abstract

A logical approach to large area sea floor strain measurement is to use a set of precision acoustic transponders interrogated successively from a large number of different positions by a near‐bottom survey vehicle. Limiting errors in such an approach can be segregated into two classes implying two different scales on which averaging should be carried out. First are those arising from individual travel time and vehicle depth measurements. Second are those associated with imperfect knowledge of the sound propagation speed. The first are essentially independent from one measurement to the next; for the second, statistically independent observations must be separated by the order of 100 m. Several thousand observations of successive travel times to individual transponders would thus be smoothed to produce the equivalent of a smaller number (few hundred) of sets of simultaneous range observations, and then these sets would be used to determine the transponder array geometry. Computer simulations using realistic assumptions show that centimeter‐level accuracy can be achieved over areas several kilometers across.     

基于倒置声学基阵的INSUSBL组合导航算法研究

文中关注水下潜航器导航定位时,电磁波传播途径中能量衰减、惯导系统长航时积累误差以及提高水下潜航器定位精度等问题。基于倒置的超短基线声学基阵,分析声波往返传播时间(RTT)、平面波近似方法和USBL导航解算方法及其坐标转换过程,结合INS误差方程,建立INS/USBL松组合模型。为进一步提高系统精度、动态性能和抗干扰性,考察USBL的原始斜距、斜距差以及声学基阵的空间分布信息,提出基于USBL原始输出信息的INS/USBL紧耦合组合导航方法。通过MATLAB仿真对导航算法进行验证,结果表明两种算法能充分抑制纯惯导误差随时间积累问题,且有效地估计出姿态、速度和位置误差角;其中紧耦合方法状态估计误差最小,导航参数精度相对松组合提高30%以上,对于提高水下载体导航定位精度、海洋探测具有重大意义。     

Sidescan sonar image processing techniques

A four-step processing sequence is described to produce image mosaics from the various segments of a sidescanned acoustic imaging survey of a given seafloor area. Starting with data consisting for each ping of acoustic backscatter levels versus horizontal range across-track, median prefiltering is used first to reduce the influence of outliers on subsequent linear processes. Artifacts that are clearly unrelated to the backscattering properties of the seafloor are then isolated on a ping by ping basis through a spectral analysis that relies on a decomposition using Chebyshev polynomials to filter the low spatial frequency components of the image. Contrast enhancement is then achieved through an original implementation of the classical gray level histogram equalization technique by balancing local versus global histogram contributions. Pixels are mapped on a geographic grid taking due account of the geometry of the measurement and of the spacing between pings to minimize along-track smearing of features. Examples of results obtained with these processing techniques are given for SeaMARC II data recorded during a complete survey of Fieberling Guyot (32°.5 N, 128° W)     

Autonomous underwater vehicles - challenging developments and technological maturity towards strategic swarm robotics systems

ABSTRACT

Reliable power supply, precise position determination and effective communication are the key requirements for strategic autonomous underwater vehicles (AUV) involved in long duration scientific missions, search operations and when operated as a swarm. The paper presents the challenging range of AUV developed for deep water, Polar and intervention applications; demanding technical requirements for strategic AUV; reliability modeling done on the lithium-ion batteries to identify the redundancy requirements for achieving near-zero failures; navigation model to estimate the achievable level of position accuracies using the state-of-the-art navigation system; limitations in underwater communication; and their importance in realizing vehicle autonomy and swarm intelligence. It is identified that a strategic grade Doppler velocity- aided inertial navigation system could provide position accuracies of about 0.5% of the distance travelled when navigated using sea bottom or ice reference, and a 38?kWh lithium-ion battery pack requires about 7% redundant battery capacity to achieve a failure probability of <?1% in a period of 1 year.     

The Impact of Multipath on High-Resolution SAS Image Statistics

As with traditional sonar, synthetic aperture sonar (SAS) is susceptible to multipath contamination, reducing the quality and also modifying the statistics of the image. Such multipath contaminants may either be environmentally induced, as is often the case when attempting to image ranges greater than the water depth resulting in returns from the boundaries, or may be induced by the system's supporting structure itself. A clear understanding of such statistical impact is necessary to advance synthetic aperture formation algorithms and for predicting system performance. Broadband acoustic data suitable for SAS processing collected with a rail-mounted mobile-tower as part of the U.S. Office of Naval Research (ONR)-funded Sediment Acoustics eXperiment 2004 (SAX04) are analyzed in this paper. Analysis focused on both system structure and environmentally induced multipath using the $K$ -distribution shape parameter as a metric. High-resolution sonar imagery often exhibited significantly non-Rayleigh, heavy-tailed envelope statistics, characterized by a low equivalent $K$-distribution shape parameter. Analysis showed a clear and significant increase in the estimated shape parameter in the presence of multipath, representing a trend toward a Rayleigh-distributed envelope. A model for reverberation is presented to provide bounds of the statistical impact using observable image intensity level increases in synthetic-aperture-formed images caused by multipath contamination. This model further shows potential for statistical impact when multipath arrivals are of similar level as the direct path even when not observable in the image (e.g., within 10 dB).      

Position Correction Using Echoes From a Navigation Fix for Synthetic Aperture Sonar Imaging

In synthetic aperture sonar (SAS), the platform position must be known sufficiently accurately for signals to be added coherently along the synthetic aperture. Often, the onboard navigation system is insufficiently accurate by itself, so corrections are needed. A well-known method is the displaced phase center antenna (DPCA) procedure for correcting platform position using seabed echoes. DPCA methods have the advantage of insensitivity to changing interference patterns, moving specular reflection, and changing occlusion, with aspect. However, when seabed echoes are unusable, either because they are too weak, or because they are corrupted by multipath, the seabed DCPA method may fail. Therefore, we present an alternative DPCA method using sonar echoes from a suitable navigation fix, based on an object detected after standard beamforming. In our proposed system, look angle is obtained by tracking the centroid of the rectified image of the fix object. When the standard DPCA correction equations are modified for a fixed reflector, it turns out that they provide incremental range and look-angle errors, precisely the values required when the target itself is used as the navigation fix. Moreover, the values obtained are then self-compensating for errors in estimating seabed depth or forward motion of the platform. The navigation fix is selected by bracketing in range, and beamforming overlapping subsets of the receiver array. In this paper, we present experimental results at transmitter frequencies of 25 and 100 kHz where our method enabled well-focused SAS images to be generated with little recourse to other navigation information. Hence, SAS can be carried out, even when a sophisticated inertial navigation system (INS) is not available.      

Acoustic mapping of fish aggregation areas to improve fisheries management in Las Perlas Archipelago,Pacific Panama

The purpose of this study was to investigate, characterize and map areas of the seabed of Las Perlas Archipelago (LPA), Republic of Panama using swath-bathymetry acoustic sonar techniques and to assess these methods as tools for feeding information into management zoning policy. In 2007 the LPA was granted conservation protection under national legislation. However, detailed management plans are still pending. Seabed mapping plays a fundamental role in identifying areas which should be prioritized within the management framework. Visual representation of habitat maps provides an effective medium for involving stakeholders in a co-management arena. In this survey, acoustically mapped areas of the seabed were ground-truthed using a combination of benthic grab samples, drop-down video and diver observations. The resulting mapped areas were then incorporated into a Geographic Information System (GIS) for further analysis. The output was a physical characterization of the seabed at three locations selected for being areas of high rugosity (habitat complexity) and, therefore, their potential importance as valuable fish aggregation sites. The rocky reefs and rhodolith beds identified in this survey represent particularly important fish aggregation and nursery habitats which should be considered priorities for protection under the management plans. This survey demonstrated the use of acoustic techniques to spatially resolve topographic features and physical characteristics of the seabed, illustrating their potential value as tools for fisheries management and marine reserve zoning in Las Perlas Archipelago and elsewhere.     

A long‐range and high‐resolution underwater acoustic positioning system

Abstract

It is desired to track the location of an underwater data collecting platform using acoustic range data. A long‐range and high‐resolution acoustic system for underwater locating has been investigated. The system provides continuous and highly accurate tracking of a platform referenced to bottom‐mounted buoys. Each reference buoy contains an acoustic transponder, which is used to obtain ranging data from the transponder to the platform. The transponder has a signal source that is phase‐modulated by a maximal‐length binary sequence and a correlation processing unit to be capable of detecting received acoustic signals with high SNR in a noisy environment or in attenuation due to long‐range propagation, and to identify multipath acoustic signals. The acoustic system has been designed and sea tests tried. The results of that experiment have yielded capability of a submeter underwater acoustic positioning system.     

Track Parameter Estimation from Multipath Delay Information

It is desired to track the location of an underwater acoustic source with range difference measurements from a stationary passive array. Many times, the array has only one or two sensors, and the multipath and intersensor range difference measurements are insufficient to localize and track a source moving along an arbitrary path [1]. Here, we propose to track sources with one- or two-sensur stationary passive arrays by making the simplifying assumption that the source's path can be described by a small set of so-called track parameters. Range difference information can then be used to estimate the track parameter set rather than the source location as a function of time. In this paper, we choose the track parameters to specify a straight-line constant-velocity constant-depth path. Cramer-Rao bounds are presented for estimating these track parameters from the time history of multipath and intersensor range difference measurements. It is shown that this track parameter set cannot be accurately estimated from the time history of a single multipath range difference without side information (an independent velocity estimate, for instance), although multipath and intersensor range difference measurements from a two-sensor array are generally sufficient to estimate the track parameter set. Computationally efficient techniques are presented which estimate track parameters from range difference measurements taken from one- and two-sensor arrays. Monte-Carlo simulations are presented which show that these techniques have sample mean-square error approximately equal to the Cramer-Rao bound when a single multipath range difference and an independent velocity estimate are available. The sample mean-square error is shown to be in the range of two to ten times the corresponding Cramer-Rao bounds when these techniques are applied to two-sensor range difference data.