Robust particle filter based on Huber function for underwater terrain‐aided navigation

Abstract

Terrain-aided navigation (TAN) is a promising technique to determine the location of underwater vehicle by matching terrain measurement against a known map. The particle filter (PF) is a natural choice for TAN because of its ability to handle non-linear, multimodal problems. However, the terrain measurements are vulnerable to outliers, which will cause the PF to degrade or even diverge. Modification of the Gaussian likelihood function by using robust cost functions is a way to reduce the effect of outliers on an estimate. The authors propose to use the Huber function to modify the measurement model used to set importance weights in a PF. They verify their method in simulations of multi-beam sonar in a real underwater digital map. The results demonstrate that the proposed method is more robust to outliers than the standard PF (SPF).

Robust Terrain-Aided Navigation through Sensor Fusion

“…By this, KF implementations, which were more common before the year 2000, have nowadays mainly been replaced by implementations of PFs and Point Mass Filters (PMF) [7]. We apply the multi-hypothesis filtering method PF, with the ability to tackle the mentioned difficulties [8], [9].…”

“…It has been shown many times that a PF can estimate the position by comparing the bottom depth with a known highresolution 3D-terrain map [8]- [15]. Many of these references focus on a use-case for Autonomous Underwater Vehicles (AUV) [9]- [15], where it is of particular importance to be able to navigate without a GNSS system. An AUV is typically equipped with a multibeam sonar in order to map the seabed, and as the equipment is already available, it has also been used for the PF [9]- [13].…”

“…Many of these references focus on a use-case for Autonomous Underwater Vehicles (AUV) [9]- [15], where it is of particular importance to be able to navigate without a GNSS system. An AUV is typically equipped with a multibeam sonar in order to map the seabed, and as the equipment is already available, it has also been used for the PF [9]- [13]. We use a single-beam echosounder instead, which makes the use-case relevant for a more substantial portion of ships.…”

“…Another difficulty that generally is not mitigated is that a PF is vulnerable to outliers in the maps or depth measurements. Peng et al point out that these outliers can occur in many ways, and they describe how to alleviate the effect by using the Huber function when setting the importance weights for the PF [9].…”

Navigation error prediction for UWAN based on AUV

“…Autonomous underwater vehicle (AUV) is widely used in many fields, such as marine investigations, underwater detection and alert, subsea engineering construction, and maintenance [1–3]. The high‐precision location information is the basic guarantee of these tasks above.…”