Meaning
An array of precomputed values replaces runtime calculations with a direct array indexing operation in embedded systems. This technique saves computational cycles by exchanging processing time for memory space. When using look up tables, the processor retrieves the results of complex functions or nonlinear sensor curves by mapped memory address rather than executing complex math.
Memory Allocation
Storing precalculated data requires careful planning of the available memory blocks on the microcontroller. Developers often place look up tables in non-volatile flash memory to preserve precious random-access memory for dynamic variables. In cases where speed is the primary constraint, copying the tables to internal static RAM during initialization allows for the fastest possible read access, which is essential for real-time control loops.
This storage strategy must balance the size of the array against the total available flash, ensuring that the code itself has enough room to compile and execute.
Sensor Linearization
Nonlinear signals from thermistors or analog sensors require conversion into linear engineering units. By implementing look up tables, the firmware can translate raw analog-to-digital converter readings directly into temperature or voltage values. This approach eliminates the need to calculate high-order polynomials on a processor without a floating-point unit, which substantially reduces the execution time of the sensor scanning routine.
Interpolation Method
Trading resolution for memory footprint is a common optimization strategy in resource-constrained devices. When the input value falls between two entries, linear interpolation is applied to calculate the output from look up tables. This method allows engineers to use smaller tables while still maintaining acceptable measurement accuracy, which ensures the system operates within its available resources.