Range-speed mapping and target-classification measurements of automotive targets using photonic-radar
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Range‑speed mapping and target‑classification measurements of automotive targets using photonic‑radar Vishal Sharma1 · Sergey Sergeyev1 · Love Kumar2 · Hani J. Kbashi1 Received: 10 June 2020 / Accepted: 16 September 2020 © The Author(s) 2020
Abstract The frequency-modulated continuous-wave radar is an ideal choice for autonomous vehicle and surveillance-related industries due to its ability to measure the relative target-velocity, target-range, and target-characterization. Unlike conventional microwave radar systems, the photonic radar has the potential to offer wider bandwidth to attain high range-resolution at low input power requirements. Subsequently, a frequency-modulated continuous-wave photonic-radar is developed to measure the target-range and velocity of the automotive mobile targets concurrently with acceptable rang resolution keeping in mind the needs of the state-of-the-art autonomous vehicle industry. Furthermore, the target-identification is also an important parameter to be measured to enable the futuristic autonomous vehicles for the recognition of the objects along with their dimensions. Therefore, the reported work is extended to characterize the target-objects by measuring the specular-reflectance, diffuse-reflectance, the ratio of horizontal-axis to vertical-axis, refractive index constants of the targets using the bidirectional reflectance distribution function. Furthermore, the reflectance properties of the target-objects are also measured with different operating wavelengths at different incident angles to assess the influence of the operating wavelength and the angle at which the radar-pulses incident on the surface of the targets. Moreover, to validate the performance of the demonstrated work, a comparison is also presented in distinction with the conventional microwave FMCW-RADAR. Keywords FMCW · Photonic-radar · RADAR · LRCS · BRDF
1 Introduction Recent developments in sensor technology, imaging, radar, light detection and ranging, electronics, and artificial intelligence have enabled the state-of-the-art autonomous vehicles (AVs) to provide significant services including collision avoidance, blind-spot monitoring, lane departure warning, or park assistance (Bimbraw 2015; Self-Driving Cars * Vishal Sharma [email protected] 1
Aston Institute of Photonic Technologies (AiPT), School of Engineering and Applied Science, Aston University, Birmingham B4 7ET, UK
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DAVIET, IKG Punjab Technical University, Kapurthala, Punjab, India
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Explained). To synchronize the operation of such systems through sensor-fusion allows the self-driving vehicles to monitor their surroundings and take evasive actions to prevent the probable road hazards (Self-Driving Cars Explained; Thrun 2010). To attain these objectives, the measurement of target-velocity and range concurrently with high precision is essential. This can be performed with the knowledge of signal processing Doppler shift (Tsui 2004; Haykin 2006; Scheer and Kurtz 1993). Therefore
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