CyberTRIZPEDIA

Payload Field of View vs Spatial Resolution

Use wide-area detection to identify regions of interest, then apply high-resolution sensing selectively to maximize coverage without proportional data growth.

CyberTRIZ analysis · Space contradiction SDP021 · one of 8,235 worked contradictions published by CyberTRIZ.AI

Regulations

Business Context

Space-based imaging and sensing missions often benefit from observing larger areas during each acquisition. A wider field of view increases coverage and can reduce the number of observations required, but maintaining high spatial resolution across a larger area can require larger optical systems, more detector elements, greater processing capacity, and increased data volume. Restricting coverage preserves resolution but reduces mission productivity.

Space TRIZ Resolution

Rather than requiring maximum resolution uniformly across the complete field of view, sensing architectures can allocate resolution according to information value. Wide-area detection can identify regions of interest, followed by targeted high-resolution observations. Multiple coordinated sensors, variable-resolution imaging, scanning architectures, and onboard processing can combine broad coverage with localized precision.

Applicable TRIZ Principles

Principle 1 – Segmentation separates wide-area detection from detailed observation.

Principle 3 – Local Quality applies maximum resolution only where information value requires it.

Principle 23 – Feedback uses initial observations to determine where subsequent high-resolution sensing should occur.

Expected Outcome

Greater geographic coverage

Maintained high-value spatial resolution

Reduced unnecessary data generation

Improved payload productivity

Decision Indicators

Early indicators include:

Higher resolution significantly reduces achievable coverage.

Large quantities of high-resolution data contain limited useful information.

Observation schedules require repeated passes to cover large regions.

Maximum resolution is applied uniformly regardless of target value.

Data volume grows faster than useful information output.

TRIZ principles applied

P1 SegmentationP3 Local qualityP23 Feedback