GPS-Denied Navigation

The GNSS dependency challenge

Since the advent of GNSS, global navigation across air, land, and sea has undergone a revolution. From commercial aircraft and maritime vessels to smartphones and autonomous vehicles, modern systems have become almost entirely dependent on GNSS for real-time, high-accuracy positional information. Its widespread adoption has been driven by the low size, weight, power, and cost (SWaP-C) of GNSS receivers combined with their unparalleled accuracy.

However, GNSS has also become a victim of its own success as many systems have become over-reliant upon it – and therefore vulnerable. GNSS signals are inherently weak and highly susceptible to jamming, spoofing, and environmental interference. In critical scenarios – such as contested military environments, urban canyons, subterranean spaces, or indoors – GNSS may be unreliable or unavailable altogether. The result is a growing need for resilient, autonomous navigation systems that can operate independently of GNSS.

Every approach to Alt-Nav has its own advantages and disadvantages.

Our design approach carefully considers mission-specific factors such as power consumption, size, weight, and the target operational environment, to deliver the best solution.

In the field of Alternate Navigation, no single sensor can guarantee reliable navigation under all conditions. Inertial Measurement Units (IMUs) excel at tracking short-term motion without relying on external signals but accumulate drift over time. Magnetic compasses provide heading information yet are susceptible to system biases or local magnetic interference. Radar can deliver precise range and bearing to nearby objects, though performance degrades in cluttered environments or rough weather. And while GNSS offers high accuracy in open conditions, it is increasingly vulnerable to jamming, spoofing, and signal degradation in contested or denied areas.

To maximize the effectiveness of these individual technologies, integration is key. At the heart of our approach is our advanced data fusion capability. Our proprietary Particle Filter algorithm is specifically engineered to handle non-linear sensor data, making it exceptionally well suited to fusing disparate sources such as visual scene matching, terrain profiling, and inertial data. Fusing multiple sensor sources together enables us to deliver navigation solutions with high reliability and adaptability in uncertain conditions.

In addition to developing the core navigation technologies and fusion algorithms, Plextek has created a powerful Data Merging Framework. This in-house simulation environment allows us to: model and simulate how a platform with a given set of sensors for PNT is likely to perform under different conditions. By rapidly understanding how a system is likely to perform with a given set of sensors, we can make informed decisions about what sensors are required to achieve a desired performance level for PNT.

Accurate modelling significantly reduces development time and cost, while also enabling high-confidence predictions of real-world systems.

“Plextek understands the unique challenges of maintaining accurate navigation when GNSS signals are degraded or denied. With deep expertise across a broad range of sensing technologies and platforms, we are well equipped to integrate the optimal combination of sensors to meet your navigation requirements – within your operational and environmental constraints.

Our strength lies in the ability to model and simulate complex scenarios, enabling us to rapidly and cost-effectively predict the right sensor mix to achieve the desired level of performance. This reduces risk and accelerates decision-making during system design.

We also excel in rapid prototyping, leveraging cross-disciplinary expertise to develop and test solutions quickly and iteratively. This allows us to validate performance in real-world conditions early in the development process.

Finally, with proven in-house design and manufacturing capabilities, we deliver fully engineered, qualified navigation systems that meet the most demanding standards for performance, reliability, and integration.”

Professor Aled Catherall, CTO