SBIR/STTR Research Award

Performance Prediction for Airborne Passive Multistatic Radar

Award identifier b2d402d62aea2a3062d94e598fde83dc95ed9e79bc8a8054e00409d9aa82b37dAwarding agency Department of Defense · Air Force

Award amount

$747,013

Program and phase

SBIR · Phase II

Award year

2013

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
MATRIX RESEARCH INC
Proposal award date
2013-04-25
Contract end date
2015-07-30
UEI
NN7YUFMM88M7
Solicitation number
2012.1
Topic code
AF121-163

Research abstract

ABSTRACT: Interest in bistatic radar, where the transmitter and receiver are not collocated, has historically waxed and waned, and is once again enjoying a resurgence. A multistatic system is one where multiple transmit sites or multiple receive sites, or both, are used to construct the radar picture. A passive radar system is one where the radar designer and user do not control the radio frequency (RF) transmissions. This effort will develop a capability to model and predict the performance of bistatic and multistatic radar systems using one or more airborne receivers and one or more airborne or ground-based transmitters. Radar modes to be analyzed include Air Moving Target Indication (AMTI), Ground Moving Target Indication (GMTI), and Synthetic Aperture Radar (SAR). A capability to model and predict the performance of these systems is critical to future development and deployment. Analysis of airborne multistatic systems is significantly more complex than that of ground-based systems. The problem also becomes more difficult when the goal is passive operation; however, being passive provides added survivability since there are no transmitted waveforms to be detected. Passive radar systems have traditionally been developed to exploit a particular emitter. The vision of future systems is to adapt to the local RF emitters, dynamically developing a passive radar strategy which is suitable to the local RF environment. The algorithm which does this may be referred to as an Illuminator Selection Manager, and passive radar performance prediction is a critical component. A performance prediction model will also allow an assessment of the military utility of such systems by providing inputs to higher level simulations. The models developed under this effort should include the effects of items such as apertures and receivers, transmitted waveforms, signal processing algorithms, clutter, and relative motion of the transmitter, receiver, and target. The models should allow parameters describing the various aspects of the system performance to be easily varied. With this construct the models should easily accommodate different instantiations of multistatic radar systems past, present, and future. BENEFIT: Anticipated benefits include increased capability to design passive multistatic radar systems, assess threat systems, and develop illumination selection managers.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

43 SBIR/STTR records share this UEI (2008–2025). Reported award amounts total $24,568,926. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense

Contractor profile

MATRIX RESEARCH INC

Historical federal award activity, when published, is on that contractor profile. Matched by UEI only.

Agency intelligence

Department of Defense

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