Advancements in sensor technology, imaging, light detection and ranging, electronics, and artificial intelligence have enabled state-of-the-art autonomous vehicles (AVs) to provide several significant services including collision avoidance, blind-spot monitoring, lane departure warning, and park assistance. The synchronization of these technologies-based driving assistance systems (DAS) allows self-driving vehicles to monitor their surroundings and respond promptly to prevent any road hazard. As a part of these objectives, the measurement of target velocity and range concurrently with high precision becomes essential in today’s AV industry. Therefore, most of the advanced AVs are equipped with various expensive signal processing modules, high precision cameras, radar, and high-end sensors. However, they still offer the target-detection to a few meters only with a limited range- and imagery resolution. The situation becomes more serious under bad weather conditions and augments the probability of road hazards.
It has been predicted that about 1.35 million people around the world have lost their life due to road accidents and ≈ 20-50 million people are surviving with critical damages. If this current tendency persists, it is predicted that road accidents may increase by ≈ 65% and turn out to be the fifth major reason for fatality by 2030. Moreover, the direct estimated costs due to road-accident injuries have been ≈ 1%, ≈ 1.5%, and ≈ 2% of the total revenue of under-developed, developing, and well-developed countries respectively. To reduce these numbers, AV-related industries are looking for some effective approaches for the last few years to improve the accuracy of self-driving vehicles with extended target-range detection and range-visibility at low-power requirements. The photonic radar (PHRAD) comes out as an attractive candidate to provide an accurate and improved range-speed resolution with low power requirements for intelligent transportation systems (ITS), remote-sensing, and other related surveillance industries. On the other hand, the existing advanced microwave-based surveillance and navigation systems are limited to a marginal accuracy range, especially, in populated areas at high frequencies.
Keeping in mind the current requirements of the advanced AVs, the importance of the photonic-radar upturns significantly by providing high range-speed resolution with precision along with an extended tracking range. However, such radars were developed at ≤ 24 GHz.
Subsequently, a tunable multiband PHRAD is the demand of the futurist AV-related industries for reducing the weight, cost, and size of the system and offers high-frequency flexibility. Such systems can be tuned to multi-frequency bands to catering to the issue of signal fading in the presence of harsh weather situations. At a high-frequency band under the impact of harsh atmospheric fluctuations, the detection range will reduce and identification of the target will be difficult to retrieve. So, a tunable PHRAD can be tuned to a low-frequency band for satisfactory performance of the photonic radar. Alternatively, it can work significantly under normal situations at higher frequency bands and offering improved radar imaging and tracking. Keeping these issues and requirements of the state-of-the-art AV-related industries in mind, the primary objective of this multidisciplinary project “Photonic Radar (PHRAD)” is to develop a multiband photonics-based radar system in 74 GHz-77 GHz frequency band for detection and ranging of multiple mobile automotive targets differentiated by their associated radar cross-section under normal and complex traffic scenarios in the presence of weak-to-severe atmospheric fluctuations. The tunability of the PHRAD over different frequency bands is attained by incorporating an experimentally designed tunable dual-wavelength fiber laser in a lab environment, which is capable to generate phase-stable millimeter waves over a wide range (≈ 12 GHz-110 GHz).
