Adaptive Sensor Management
AI Overview
The Navy seeks an adaptive algorithm that automatically optimizes sensor resource allocation across ship defense radar systems. The solution must dynamically identify which sensors contribute most to tracking threats and redirect underutilized sensor capacity to improve overall combat system situational awareness and engagement readiness.
This summary is AI-generated from the official solicitation.
Key Details
Official Description
Navy aircraft carriers and amphibious warfare (L-class) ships are defended by the SSDS, a combat system comprised of weapons, sensors, communications systems, computers, and other elements working together to detect, track, and engage inbound anti-ship missiles and other threats. SSDS platforms sense their environments and identify tracks of interest by integrating inputs from a variety of sensors, which include rotating, fixed face and fire control or target illumination radars that cover a var...
Change History
Adaptive Sensor Management
**Q&A Addition:** One new answer added to Q1 clarifying that specific quantitative track quality metric thresholds will NOT be provided; performers must propose and justify representative metrics for Phase I. Reference materials will be unclassified, "low-to-medium" fidelity documentation describing functional/conceptual system-level constraints rather than detailed executable models. No formal baseline allocation policy exists; goal is demonstrating improvement over current static, rule-based behavior.
Adaptive Sensor Management
**Summary of Q&A Changes:** Q2 received a new answer clarifying that a decision table alone is insufficient for Phase I—analytical output is required. Also states track quality and resource-utilization thresholds are not provided in Phase I; solutions must be dynamic with hard requirements coming in Phase II. Q3 (new question) answered with four key clarifications: (1) generic optimizer acceptable if it accounts for sensor-specific traits; (2) algorithm runs continuously on event-driven basis; (3) proposer can choose optimization timeframe approach; (4) solutions must be dynamic, adaptive, responsive to rapid track hostility changes, and handle heterogeneous sensor combinations.
Adaptive Sensor Management
# Q&A Changes Summary **Added 3 new questions:** - Q1: Track quality metrics authoritative for constraints, threshold definitions, and Phase I expectations - Q2: Level of detail in reference architecture materials (resource models, sensor specifics, classification level) - Q3: Baseline SSDS tasking doctrine and preferred format for explainability artifacts **Reorganized:** Original Q2 (decision demonstration table) moved to new Q2 position; original Q2-Q3 (optimization details) moved to Q3, consolidating into single question block. **Key clarifications added:** Track quality metric definitions, reference material scope/detail, sensor resource model specifics (beam scheduling, dwell budgets, revisit constraints), classification level, and baseline comparison criteria.
Adaptive Sensor Management
**Added Q1** requesting Government approval of a decision demonstration table approach (with specific sensor examples: SPS-48, SPQ-9B, MK-9, SPY-6(V)3) as Phase I feasibility demonstration, and asking for preferred track-quality or resource-utilization metrics.
Adaptive Sensor Management
This Q&A clarifies that Phase 1 can use a generic, sandbox-environment optimizer rather than requiring sensor-specific implementations, and seeks applicant input on critical design parameters (call frequency, temporal scope, novel scenarios) that should be addressed in proposals to align with Navy requirements.
Adaptive Sensor Management
Status changed from Pre-Release to Open
Adaptive Sensor Management
New opportunity: Adaptive Sensor Management
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