A 17.8-MS/s Compressed Sensing Radar Accelerator Using a Spiking Neural Network.

A prototype compressed sensing radar processor boosts the accuracy of target range and velocity estimations by over 6 $\times $ compared with conventional processing techniques. The prototype numerically solves basis pursuit denoising with a biologically plausible spiking neural network. A unique form of weight compression allows on-chip storage of all weights for the large fully connected network. Capable of producing over 200000 range-velocity scene reconstructions per second, the prototype improves throughput by 8 $\times $ and efficiency by 18 $\times $ over the state of the art. [ABSTRACT FROM AUTHOR]