Imagine living in the tropics: it’s hot, tropical, sunny and… humid, dusty, smoky and polluted. That’s the imperfect reality for many people who live and work in tropical areas, both on the coast and inland.
Smoke and dust results in haze. That may not be visible – or at least important – to a tourist on the beach. But for men and women involved in maritime patrol, law enforcement or Search and Rescue (SAR) operations, haze can be the difference between spotting a target and missing it completely, even in broad daylight – the difference between life and death.
Suspended particles reduce visibility meaning that airborne EO/IR platforms trying to support fire fighters, for example, need to get dangerously close to the flame front, often in rugged country, to detect and track assets such as fire trucks. At these altitudes the risk of collision with fire-fighting aircraft grows exponentially. The dangers are obvious.
Why? Because by reducing visibility, haze defies attempts to see through it using Electro-Optic and Infrared (EO/IR) sensors to augment or replace the human eyeball.
Hence Melbourne-based Sentient Vision Systems’ program to adapt its unique Artificial Intelligence (AI) and Machine Learning technology to Short-Wave Infrared (SWIR). The program is aimed to provide the company’s stand-off ViDAR (for Visual Detection and Ranging) capability in a challenging optical environment.
This capability will blend a SWIR sensor with AI derived from the company’s proven ViDAR product to create a sensor imagery analysis capability that has never existed before. ViDAR is a software-based imagery analysis system that examines every frame in a sensor’s high-resolution imagery feed and detects targets that would be invisible to a human operator, or very hard to spot. It offers up to 96% probability of detecting a target over the ocean and enables a patrol or SAR aircraft to cover a designated search area up to 30 times faster than one without a ViDAR sensor.
What’s so special about a SWIR sensor? It operates in the 1-3 micron waveband which gives it a unique ability to ‘see’ through atmospheric haze, whether moisture, dust or smoke. By contrast, Medium-Wave IR (MWIR) in the 3-5 micron waveband is well suited to night vision and poor visibility. Long-Wave IR (LWIR) in the 8-15 micron waveband is the traditional ‘thermal imaging’ wave band and LWIR sensors detect temperature differences with great sensitivity, but are attenuated by haze, dust and smoke.
So what? Whereas a conventional EO/IR sensor might have a range of up to 20nm in good atmospheric conditions, in a hot and hazy environment like the Gulf, its range could fall to as little as 1nm in thick haze, and even less than this in dense smoke or dust.
Using SWIR sensors increases this range considerably in hazy conditions, and the ViDAR-derived AI and Machine Learning technology means that difficult to spot targets within the sensor feed can be detected autonomously in exactly the same way as a conventional, EO or LWIR ViDAR system. ViDAR simply puts a thumbnail on the operator’s screen that provides the range and bearing of the target for closer investigation by the platform’s primary sensor.
Think what that means to operators. This capability aims to provide them with more time to act or react because they’re detecting targets from a much greater distance – a UAV might even be completely invisible and inaudible to the target it is shadowing.
On a SAR mission, survivors in the water can be detected further away; on a maritime patrol or law enforcement mission, it will be possible to detect terrorists’ vessels or illegal fishers at longer range. Over land, targets in polluted or dusty areas can be detected from a greater distance; and UAVs assisting firefighters can operate at a safe stand-off altitude, high enough that fire-fighting aircraft can safely pass beneath them. While the flame front is mapped using a Long-Wave IR on the same aircraft or UAV, SWIR can help operators watch assets on the ground such as fire trucks and help emergency managers maintain situational awareness despite the bedlam of a bush fire.
The advantages of SWIR and ViDAR to the operator are clear: it’s a passive capability, so undetectable, unlike radar. A SWIR sensor provides an EO-like image of the target, which is much easier to interpret than a radar image. The combination of SWIR and ViDAR is especially good for detecting small objects, unlike radar: ViDAR’s combination of AI and Machine Learning enables the sensor to detect and track targets a few pixels in size. So, a SWIR/ViDAR-equipped aircraft or UAV is far more productive than an aircraft without this system.
A SWIR sensor is more expensive than a standard 3-5 micron EO/IR sensor and lacks its range, but these factors are more than compensated for by the hitherto unavailable capabilities it provides in haze, dust and smoke. In any case, Sentient sees this as an adjunct to its proven EO/IR ViDAR technology, not a replacement.
For this reason, Sentient Vision Systems is exploring potential Land and Sea ViDAR SWIR applications. From an altitude of 10,000 feet over land (which means it’s invisible and inaudible to the enemy), a SWIR/ViDAR equipped UAV could maintain overwatch of friendly forces, day and night, and when required it will see through battlefield smoke and dust to identify friendly and hostile forces. At sea, operators will get the same benefit, meaning pirates, terrorists, illegal fishers and criminals can’t escape detection and scrutiny.
This won’t happen immediately, however. The process of conducting flight trials in real-world bush-fire, haze and dust storm conditions has been difficult during the COVID-19 pandemic, but with the worst effects of the pandemic expected to pass soon, this new capability is imminent.