Officials of the Naval Air Warfare Center Aircraft Division-Lakehurst in Lakehurst, N.J., chose radar experts at RDRTec Inc. in Dallas to design a common sense-and-avoid radar system for the MQ-8 Fire Scout unmanned helicopter and the MQ-4C Triton unmanned reconnaissance aircraft under terms of a $3 million contract awarded last week.
RDRTec experts will evolve and transition the Radar Autonomous Collisions Avoidance System (RACAS) Sense and Avoid (SAA) radar technology into the Common RACAS (C-RACAS) that fulfills both the Fire Scout and Triton UAS.
The sense-and-avoid radar that will be common to the two UASs is to help the unmanned aircraft avoid collisions with other aircraft with the UASs are not in contact, Navy officials say. The goal of the project is to enhance efficiency in airspace integration.
Background/Related:
Navy STTR Award
Title Maneuver Prediction and Avoidance Logic For Unmanned Aircraft System (UAS) Encounters with Non-Cooperative Air Traffic
Abstract
Air-Borne Sense and Avoid (ABSAA) cooperative sensors like TCAS and
ADS-B are non-developmental off-the-shelf items and as such their
employment should be optimized to maximize their effect on levels of
safety. The radar subsystem is a new construct whose role and employment
has not been previously defined. In addition, the cost of the radar
development and production costs are high and dependent on its assigned
role and the associated performance requirements. As such a complete
assessment of the Size Weight and Power (SWaP) and costs must be
included in the establishment of safety requirements.
Currently, the Navy is formulating the traceability between Air-Borne
Sense and Avoid (ABSAA) radar subsystem and system requirements for UAS
platforms including Triton and Fire Scout. This STTR builds on and is
coordinated with that effort but focuses on a specific radar ABSAA
subsystem, the Common Radar Automatic Collision Avoidance System
(C-RACAS) in order to support its development schedule. C-RACAS is
targeted for both the Fire Scout and Triton platforms.
Navy SBIR Award
Title Processor Architectures for Multi-Mode Multi-Sensor Signal Processing
Abstract
RDRTec Inc. proposes to enhance imaging modes to improve performance
of Maritime and Overland Classification Aids (MOCA). In addition, this
effort will further mature innovative processor and processing
architectures that enable the Fire Scout Radar Autonomous Collisions
Avoidance System (RACAS) to be FAA certified for operation in the Nation
Air Space (NAS) as well as add simultaneous tactical modes.
The Maritime and Overland Classification Aids (MOCA) project enables an
accelerated capability development for Intelligence, Surveillance, and
Reconnaissance (ISR) missions and advanced radar enhancements for
surface operations. Capability enhancements include improved radar
imaging, tracking, and classification of surface contacts as well as
more efficient sensor utilization and improved operator interfaces.
RACAS is currently under development by ONR and NAVAIR as a Sense and
Avoid (SAA) initiative for transition into the MQ-8. Analysis has shown
that RACAS antenna hardware could be upgraded so as to simultaneously
support both SAA and tactical modes; however, these must be implemented
so as not to cause undue additional DO-178 and DO-254 certification cost
as required by the Federal Aviation Administration (FAA) for SAA.
Navy SBIR Award
Title Adaptive Radar Detection Approaches for Low-RCS Maritime Vessels in Highly Variable Clutter Conditions
Abstract
This propose effort will determine the feasibility of and continue
development of innovative methods in support of simultaneous tracking
and imaging for Pulse Doppler radar systems. Future missions of airborne
ISR radar systems will require detection of moving targets in the
presence of clutter, jamming, and other background interference noise
using the maritime moving target indicator (MMTI) waveform and to
automatically classify the targets using high resolution imaging
waveforms such as high range resolution (HRR) and inverse synthetic
aperture radar (ISAR). As computational capabilities become
increasingly available, the use of advanced signal processing software
to simultaneously process radar data for the purpose of detection and
automatic target recognition (ATR) becomes more practical.
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