Condition-Based Loading of Collision Avoidance Data Subsets
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Solution Overview
Problem
Current collision avoidance and detection systems for aircraft, such as TCAS and ACAS, require large data structures that are time-consuming and power-intensive to load into memory, posing challenges for small aircraft like drones with limited power, size, and weight constraints.
Innovation Solution
An electronic device loads a subset of the collision avoidance and detection data structure based on current conditions like position and speed, using non-volatile memory for storage and volatile memory for operation, reducing load time and power consumption, and allowing for dynamic adaptation of the subset.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the complete collision avoidance and detection data structure is loaded into DRAM, then collision avoidance accuracy is improved, but power consumption and load time increase significantly
Solution Approach 1:
The patent divides the large collision avoidance data structure (2-16 GB) into smaller subsets that can be selectively loaded into DRAM based on current flight conditions. Only the necessary subset corresponding to the aircraft's current position, altitude, and flight parameters is loaded, reducing memory requirements from 16 GB to potentially much smaller amounts while maintaining accurate collision detection for relevant scenarios
Solution Approach 2:
The system pre-identifies which subset of the data structure will be needed based on current flight conditions before loading occurs. By determining the required subset in advance based on position, altitude, and flight parameters, the system prepares only the necessary data for upcoming collision detection scenarios, avoiding loading unnecessary data that would consume power and time
2Measurement precision
If the complete collision avoidance and detection data structure is loaded into DRAM, then collision avoidance accuracy is improved, but load time increases to 2-5 minutes
Solution Approach 1:
The patent segments the 2-16 GB data structure into manageable subsets that can be loaded quickly into DRAM. By loading only the relevant subset based on current flight conditions rather than the complete data structure, the load time is reduced from 2-5 minutes to a much shorter duration, enabling rapid deployment on small aircraft while maintaining detection accuracy for applicable scenarios
Solution Approach 2:
The system determines which data subset will be required based on current position, altitude, and flight parameters before the loading process begins. This preliminary identification ensures that only necessary data is transferred from non-volatile storage to DRAM, minimizing load time while ensuring the correct data is available for collision avoidance operations
3Adaptability or versatility
If the complete collision avoidance and detection data structure is loaded into DRAM, then collision avoidance coverage is improved, but aircraft size and weight increase
Solution Approach 1:
The patent segments the comprehensive 2-16 GB data structure into condition-specific subsets. Small aircraft can load only the subset relevant to their operating conditions (position, altitude, speed ranges), reducing the memory capacity required and consequently the weight of the memory subsystem while maintaining adequate collision avoidance coverage for their specific flight envelope
Solution Approach 2:
The system dynamically selects which data subset to load based on real-time flight conditions including position, altitude, and speed. This dynamic adaptation allows the collision avoidance system to maintain comprehensive coverage for the aircraft's current operational context without requiring the full data structure to be permanently resident in heavy DRAM memory
4Reliability
If the complete collision avoidance and detection data structure is loaded into DRAM, then detection capability is improved, but power consumption increases for small aircraft
Solution Approach 1:
The patent segments the data structure so that only the portion needed for current flight conditions is loaded into power-consuming DRAM. This maintains reliable collision detection for scenarios relevant to the aircraft's current position and flight parameters while avoiding the continuous power consumption associated with maintaining the entire 2-16 GB data structure in volatile memory
Solution Approach 2:
The system pre-determines which data subset will provide adequate detection capability for current flight conditions before loading. By identifying the necessary data based on position, altitude, and speed parameters in advance, the system loads only what is needed for reliable detection in the current operational context, minimizing power consumption while maintaining detection reliability
Data Source
AI summary
An electronic device is described. This electronic device may include: a first type of memory that stores a collision avoidance and detection data structure having a predefined size, a second type of memory, and a processor. For example, the first type of memory may include a volatile memory (such as flash memory), and the second type of memory may include a non-volatile memory (such as dynamic random access memory or DRAM). During operation, the electronic device may access, in the first type of memory, a subset of the collision avoidance and detection data structure based at least in part on current conditions, where the subset is less than the predefined size, and the current conditions include a position and speed of the electronic device. Then, the electronic device may load the subset from the first type of memory to the second type of memory.