Sense and Avoid Airborne Radar Implementations on a Low-Cost Weather Radar Platform

Abstract

Traditionally, multi-mission applications in airborne radar are implemented through very expensive phased array architectures. The emerging applications from civilian surveillance, on the other hand, prefer low-cost and low-SWaP (space, weight and power) systems. This study introduces a software-based solution that intends to use low-cost hardware and advanced algorithms/processing backend to meet the remote sensing goals for multi-mission applications. The low-cost airborne radar platform from Garmin International is used as a representative example of the system platform. The focus of this study is the optimal operating mode, data quality and algorithm development in cases of all-weather sense and avoid (SAA) applications. The main challenges for the solution are the resolution limitation due to the small aperture size, limitations from the field-of-view (FOV) and the scan speed from mechanical scanning. We show that the basic operational needs can be satisfied with software processing through various algorithms. The concept and progress of polarimetric airborne radar for dual-function operations at X-band Generation 1 (PARADOX1) based on the platform are also discussed.

Risk Assessment Method for UAV’s Sense and Avoid System Based on Multi-Parameter Quantification and Monte Carlo Simulation

“…Various types of sensors can be utilized based on the method of detection required, as described in [14][15][16]. Currently, among the most commonly used sensing technologies are electro-optical (EO) cameras, Infra-red (IR) cameras, Light Detection and Ranging (lidar) sensors, and Radio Detection and Ranging (radar) sensors, as described in [17,18].…”

“…However, the SAA system's importance remains critical, as shown in [10], where numerous UAVs in high-density airspaces are simulated in a Monte Carlo simulation setup. Therefore, SAA development and advancement are always in the spotlight [11][12][13][14][15][16][17][18][19][20] when discussing UAVs' operation in the airspace system.…”

The Use of Weather Radar Data: Possibilities, Challenges and Advanced Applications

“…Li et al [34] introduce a microphysicsbased simulator applied in different weather scenarios to address the theoretical basis and uncertainties of hydrometeor scattering. Nepal et al [38] present a radar implementation on a low-cost weather radar platform for multi-mission applications. Nekrasov et al [39] developed a conceptual approach for measuring near-surface wind vectors with airborne weather radar to predict the future sea surface conditions and weather patterns.…”

Phased-Array Radar System Simulator (PASIM): Development and Simulation Result Assessment

“…The system component (antenna, T/R module, and digital backend) parameters are obtained from available commercial products. The core of the implementation is based on the MATLAB Phased-Array System Toolbox [12,13] and other toolboxes. Customized models include signal-processing modules and electronics models.…”