Terrain navigation techniques for AUV MCM operations K. B. nonsen 1 , - - PDF document

UDT 2020 Extended Abstract Ånonsen Session Autonomy at sea

Terrain navigation techniques for AUV MCM operations

• K. B. Ånonsen1, O. K. Hagen2 and H. S. Telle3

1Senior Scientist, Norwegian Defence Research Establishment (FFI), Kjeller, Norway, email:kjetil-bergh.anonsen@ffi.no 2Principal Scientist, Norwegian Defence Research Establishment (FFI), Kjeller, Norway 3Commander, Royal Norwegian Navy, Bergen, Norway

Abstract — Terrain navigation techniques, which use measurements of the sea floor together with a digital terrain model (DTM) to obtain position updates to the navigation systems, is an attractive technique in mine counter measure (MCM) operations with autonomous underwater vehicles. We show how terrain navigation can be used to facilitate submerged MCM operations without the need for surfacing for GNSS fixes or pre- deployed infrastructure on the sea floor. The concept is demonstrated using test data from one of the Real Norwegian Navy’s newly acquired Kongsberg HUGIN AUVs.

1 Introduction

Over the last two decades autonomous underwater vehicles (AUVs) have proven to be highly efficient tools for conducting underwater mine counter measure (MCM)

• perations. One of the fortes of the AUV is that it can enter

the operation area covertly, without the need for a surface vessel following it into the possibly dangerous area. The success of such operations is dependent on high accuracy AUV navigation estimates, i.e. vehicle position and attitude estimates, to be able to determine the correct positions of observed mine-like objects of interest on the sea floor. Modern AUVs partially solve the navigation problem by using inertial navigation systems, which are aided by pressure sensors and Doppler velocity logs whenever the AUV is submerged and GNSS signals are not available. In extensive submerged operations, the AUV will still need external position updates in order to keep the navigation accuracy sufficiently high. As surfacing for GNSS fixes in many cases is impractical and revealing, terrain navigation, in which measurements and knowledge of the terrain are combined to obtain a position estimate, is an attractive alternative in many scenarios.

2 AUV MCM Operations

We here focus on mine hunting operations with AUVs equipped with high-resolution side-looking sonar systems (e.g. synthetic aperture sonars (SAS)) capable of locating mine-like objects, in addition to optical cameras for identification of the contacts. The AUV can either be run from a manned surface vessel, or be part of a fully unmanned MCM system operating with an unmanned surface vehicle (USV), in accordance with [1]. In addition to the abovementioned sensors, the AUV must be equipped with a bathymetric sensor, preferably a multibeam echo sounder (MBE) or interferometric side- scan or SAS system [2], to be able to conduct terrain navigation. An AUV MCM scenario typically consists of three phases: a survey phase, a detection and classification phase and an identification phase. During the survey phase, the operation area is mapped using a side-scan or SAS system. The detection/classification phase was traditionally carried out by a human operator, but the development of automatic target recognition (ATR) systems has automated this process to a large extent [3]. The identification phase can be carried out using an optical camera on the AUV, revisiting the detected targets. This phase can either be conducted in a separate run, after the survey data have been processed, or be integrated with the

• ther phases in a single sortie [4]. In either case, a

previously surveyed area is revisited during the identification phase, which can be utilized by the terrain navigation system.

3 AUV navigation system

3.1 Inertial navigation system (INS) Modern AUVs are equipped with inertial navigation systems (INS), in which measurements from inertial sensors (accelerometers and gyroscopes) are combined with a suite of aiding sensors to counter the inherent INS

• drift. One example is the Kongsberg HUGIN AUV

navigation system [5]. 3.1.1 Core INS The core INS of a modern AUV consists of an Inertial Measurement Unit (IMU), a pressure sensor and a Doppler velocity log. This system is typically initialized using GNSS measurements before diving. While the AUV is submerged and GNSS is not available, the core INS accuracy will degrade with time due to integration of measurement noise. In [6], a submerged drift rate of 0.04-

UDT 2020 Extended Abstract Ånonsen Session Autonomy at Sea 0.08 % of traveled distance was reported. In order to maintain sufficient navigation accuracy during longer autonomous operations, the vehicle must either surface for a GPS fix or use alternative aiding methods like underwater transponders [7] or terrain navigation [8-10]. 3.1.2 Terrain navigation Terrain navigation algorithms use measurements of the terrain below or close to the vehicle, together with a digital terrain model (DTM), to find a position estimate, which can be used as a submerged update to the INS. Originally developed for aircraft and cruise missiles, terrain navigation has gained popularity for underwater vehicles

• ver the last two decades and is now an optional add-on to

the Kongsberg HUGIN AUV family [10]. This system uses a terrain navigation algorithm based on the point mass filter algorithm [11]. As a rule of thumb, in suited terrain,

• ne can expect a horizontal position accuracy comparable

to the horizontal resolution of the DTM In their standard form, the terrain navigation algorithms are dependent on the existence of a DTM prior to the operation. However, this requirement can be relaxed by using SLAM (Simultaneous Localization and Mapping) [12, 13] or SLAM-like techniques. As an example, in an MCM scenario for which no prior DTM exists, the vehicle can use a bathymetric sensor to build a DTM during the survey phase of the mission. When later returning to the same area, e.g. in order to make an optical camera identification of detected mine-like objects, the AUV can use this in-situ DTM for terrain navigation [14, 15].

4 Results

We here consider a test mission done with one of the Royal Norwegian Navy’s newly acquired Kongsberg HUGIN

• AUVs. The test was conducted in the Oslo Fjord in

Norway in January 2020, and was planned as a typical MCM mission, in which the vehicle first ran several search patterns with synthetic aperture sonar, before performing an identification phase in which the optical camera was used for identification of interesting targets. Kongsberg EM2040 multibeam data from an earlier AUV mission in the area was used to build a 5 by 5 meter gridded DTM, for use in the terrain navigation system. This DTM covered parts of the mission plan for our test, allowing the AUV to

• btain terrain navigation fixes to the navigation system

when passing over the mapped areas. The vehicle trajectory and the DTM are shown in Fig. 1.

• Fig. 1: Trajectory of the AUV mission overlaid the DTM.

The AUV navigation system was initialized using GNSS before diving and the vehicle was then run submerged for approximately 20 hours with terrain navigation as the sole position update method. After approximately 20 hours, the vehicle surfaced for a GNSS fix. The differences between the real-time estimated position (using terrain navigation) and the best available post-processed navigation solution are shown in Fig. 2, together with the estimated real-time navigation uncertainty. The post-processed navigation solution was computed using the navigation processing tool NavLab [16], and is a smoothed solution using all the GNSS, IMU, DVL and pressure measurements throughout the mission, but not the terrain navigation updates. Since this solution has a period of more than 20 hours without position updates, its uncertainty is quite high and should not be regarded as ground truth. However, as can be seen from Fig. 2, the difference between the post-processed and real-time navigation estimates stayed within the 1 sigma band of the real-time navigation system throughout most

• f the run, indicating that the real-time navigation did not

suffer from serious wild-points that were falsely accepted by the terrain navigation system.

UDT 2020 Extended Abstract Ånonsen Session Autonomy at Sea

• Fig. 2: Differences between real-time navigation estimates with

terrain navigation and best available post-processed navigation estimates without terrain navigation fixes, together with estimated 1 and 3 standard deviation bounds for the real-time navigation estimates.

Verification of the real-time navigation accuracy (using terrain navigation) when the vehicle surfaced for the GNSS fix after 20 hours can be done by comparing the real-time position with what the estimated position would have been without any terrain navigation updates, which can be found using NavLab. At the time of the GNSS fix, the difference between the GNSS position and the real- time, terrain navigation aided position was around 5 m, wheras the corresponding difference without the terrain navigation would have been approximately 16 m. Even though this accuracy is only valid at this particular time instant, it clearly indicates the value of using terrain navigation in this case. Without the terrain navigation, frequent surfacing for GNSS fixes would have benn needed in order to sustain an acceptable navigation accuracy.

5 Conclusions

In this paper, we have discussed how terrain navigation can be used in AUV MCM operations to increase the navigational autonomy and facilitate extended submerged

• perations with acceptable navigation accuracy. In an

example run conducted with one of the Royal Norwegian Navy’s newly acquired Kongsberg HUGIN AUVs, the navigation accuracy was demonstrated to be around 5 meters after more than 20 hours of operation using terrain navigation on a DTM with only partial coverage in the

• peration area. Without terrain navigation, the AUV

would need to rely on sea floor infrastructure like underwater transponders or surfacing for GNSS fixes regularly to achieve comparable navigation accuracy. Future work includes exploring new methods of

• peration to further increase the operational applicability
• f the terrain navigation system, especially how to handle

the use of within mission created DTMs properly, through relative position updates.

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UDT 2020 Extended Abstract Ånonsen Session Autonomy at Sea

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Author Biographies

Kjetil Bergh Ånonsen is a senior scientist in the navigation group at the Norwegian Defence Research Establishment (FFI). He holds a PhD in Engineering cybernetics and an MSc in applied mathematics from the Norwegian University of Science and Technology (NTNU). He joined FFI in 2007. Ove Kent Hagen is a principal scientist in the navigation group at the Norwegian Defence Research Establishment (FFI). Hagen holds an MSc in Fluid Mechanics and BSc in Mathematics from the University of Oslo. Since 1999 he has been working with underwater navigation of the HUGIN AUV, with special focus on terrain navigation. Cmdr Helge Stian Telle is an AUV specialist in the Royal Norwegian Navy. He has background from the Norwegian Naval Academy and operational experience from submarines and mine hunting vessels. The latest 18 years he has been working with HUGIN AUV systems for use in mine hunting scenarios.