Sub-Bin Resolution
Digital signal algorithms calculate the center of mass of a frequency peak to determine its location with sub-bin resolution. Applying spectral centroid interpolation to radar level data allows the system to resolve the target distance far more accurately than standard Fourier transform bin spacing. This method calculates the weighted average of the signal energy around the maximum peak.
Algorithm Mechanics
Standard digital signal processing is limited by the discrete nature of the fast Fourier transform, which divides the frequency spectrum into fixed bins. Using spectral centroid interpolation allows the processor to find the true peak frequency even when it falls between two bins. This interpolation improves the resolution by an order of magnitude without increasing the sampling size.
Sensor Accuracy
This algorithm relies on a symmetric peak shape to compute the correct weighted average. Non-symmetric returns, which can be caused by nearby clutter or noise, will skew the interpolation and introduce small measurement errors. System designers must ensure that the signal is filtered to remove these distortions before running the algorithm.
Software Testing
Software quality audits verify the interpolation math using synthetic data sets with known frequency offsets. This verification ensures that the calculated peak matches the simulated value under all noise conditions.
