SBIR/STTR Research Award

ISAR Imaging and ATR

Award identifier 63335bbc1f6d16049c01613e1c6f578d9bf8d81fb930b4ce9353ff6611d434e0Awarding agency Department of Defense · Navy

Award amount

$1,104,160

Program and phase

SBIR · Phase II

Award year

2020

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Defense
Branch
Navy
Recipient company
RDRTEC INCORPORATED
Proposal award date
2020-06-25
Contract end date
2024-02-20
UEI
JE6AK2EVH218
Solicitation number
19.1
Topic code
N191-004

Research abstract

In phase I, RDRTec studied the feasibility of applying innovative ISAR imaging and associated Automatic Target Recognition (ATR) approaches to provide classification of maritime targets suitable for autonomous verification of a missile’s target during the end stages of the missile’s flight.  This includes techniques that minimize the time required to detect, track, and classify a target of interest within a cluster of potential targets while maintaining the accuracy needed to provide the high level of Probability of Correct Classification (PCC) required for engagement.   The approach leverages RDRTec’s suite of tools, CADD & MCA, which automate the process of exploiting radar data to perform target detection and identification. RDRTec’s Coherent Airborne Detection & Discrimination (CADD) mode is a SAR mode, which in one measurement can image a large scene, detect multiple targets, screen for target types, and re-focus image chips around those detections for further analysis.  This mode will be leveraged along with traditional surveillance modes, high range resolution, short-dwell ISAR, and real-beam ISAR to minimize the required radar resource utilization aspects of the cruise missile end game scenario.  RDRTec’s Maritime Classification Aids (MCA) will be applied to identify which target within the area of interest is the correct target to be engaged.  In order to achieve a high PCC and provide human-understandable explanations, MCA uses an expert system, physics-based feature extraction which identifies characteristics such as ship length, superstructure dimensions, and rotator location & characteristics.  MCA includes a database of ships of the world which is updated monthly and does not require training data. Based on what was learned in Phase I and currently foreseen transition opportunities, Phase II will extend, mature, test and integrate ATR functionality into MCA.

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

100 SBIR/STTR records share this UEI (2006–2025). Reported award amounts total $62,250,393. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense

Agency intelligence

Department of Defense

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.