Conference Agenda

MAST Med 2022 Grand Hyatt, Central Athens, Greece

Wed 2 Nov 2022

12:00 Wed 2 Nov 2022

12:00–13:30

1B: Surface

Next Generation Navigation

GPS/GNSS Spoofing Detection and Safe Recovery

  • Dr Emmanuel Nguyen
    Engineer
    Thales
    France

Navies are facing numerous challenges in particular in the Electronic Warfare (EW) domain toward radio navigation signals. Indeed, GPS signals are subject to numerous aggressions and their complexity is increasing every day, therefore, GPS data cannot be trusted blindly anymore. TopAxyz Inertial Navigation System (INS) implements an innovative approach in the naval domain by using only fully trusted and predictable information to compute safe navigation information. This approach allows Thales to provide a complementary “layer” of protection toward GPS data usage with a new function to monitor the GPS data and detect any type of spoofing aggression. When GPS spoofing is detected, the vessel system is already corrupted with a fake position and it is complex and time consuming to come back to a safe situation. To prevent this devastating operational effect, TopAxyz INS’s unique architecture allowing multiple independent virtual INS is able to provide an accurate and uncorrupted alternative position and navigation solution when GPS spoofing is detected. Moreover, the crew has the ability to adjust TopAxyz INS Spoofing detection mechanism to take into account the operational situation and manage accordingly the false alarm rate and probability of undetected events to ensure the best compromise.

TopAxyz INS is the only navigation solution combining a mechanism to detect GPS spoofed data and propose an entirely safe recovery navigation solution.

Radar-only Autonomous Navigation in GPS Denied Environments

  • Mark Saunders
    Scientist
    Cambridge Pixel
    United Kingdom

Radar-only autonomous navigation for GPS-denied environments and for the detection of GPS Spoofing

USVs and ASVs are generally fitted with navigation radars for situational awareness and collision avoidance. In normal use, the radar is primarily used for detecting tracks which are passed to the autonomy system.

Navigation is usually performed using GPS and Inertial Navigation Systems.In the event that GPS is denied, INS alone can be used, but over time, drift will occur and positional accuracy reduces.

A system for obtaining navigational fixes from radar can be achieved by modelling the expected radar image, using public domain terrain data, and comparing it with the live radar image in an iterative manner. During normal GPS operation, the radar estimated position serves as a check for GPS spoofing. In the event that GPS fails, is denied or spoofing is detected, then an alternative source of positional fixes is available.

Cambridge Pixel has developed ‘GPS-Assist’, a software navigation solution which can either run stand-alone, or easily be added to the Cambridge Pixel radar interface and target tracking software already used by many of the USV/ASV System Integrators.This innovative solution will be described in this paper, and its application, performance and limitations discussed.

Coastal Surveillance at Scale

  • Mr Georgios Kontogiannis
    Deployment Strategist
    Lambda Automata
    Greece

Continuous real-time monitoring of large expanses of land and sea accelerates the observe-decide-act cycle. Yet doing so at scale is not possible as each observation point requires an extra operator in the loop.

Autonomous systems enable surveillance at scale. State of the art object detection neural networks outperform humans when it comes to heightened attention tasks over an extended period of time. Leveraging this fact, data from different sensors can be fused (cameras, radars, RF receivers) to reliably detect objects of interest and place their semantic representation on a single geospatial canvas.

By collating the annotated output of multiple sensors on a single operational picture, extending the monitoring grid becomes sustainable as the operating cost of the grid does not increase linearly with each new sensor added to the grid.

In our paper we cover how the existing network of sensors can become autonomous and how we can combine them with autonomous wide range perception towers to comprehensively monitor remote environments.

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