This invention provides a computationally efficient means of performing adaptive pulse compression (APC) and is denoted as the Fast APC (FAPC) algorithm. The FAPC algorithm dramatically reduces range sidelobes while maintaining near optimal signal-to-noise (SNR) gain and is much more computationally efficient than the original APC.
Pulsed radar systems transmit a waveform which, upon receive, is typically match filtered, thereby achieving a range resolution inversely proportional to the bandwidth of the transmitted waveform. Although the matched filtering maximizes the SNR, application of the matched filter results in range sidelobes that occur due to the correlation of the transmitted waveform with delayed versions of itself. Least square estimation and APC have been introduced by researchers but have robustness problems and high computation costs respectively, leaving more room for development. Researchers at the University of Kansas have developed a computationally efficient method for implementing APC.
This technology can be utilized in radar applications where small targets are masked in the sidelobes of the larger targets.
This technology uses reduced dimensionality techniques to alleviate the computational burden of APC. This is achieved by the new algorithm denoted as FAPC. The two embodiments of FAPC are derived by segmenting the original APC MMSE cost function by forming blocks of contiguous samples, or by forming segments using decimated samples.
The FAPC algorithm greatly reduces the computational cost of APC while maintaining acceptable (near optimal) performance. The computation per stage of FAPC can be as low as that of the matched filter while parallel processing is utilized.
The FAPC method can significantly reduce computational complexity while maintaining acceptable SNR performance. The order of computational complexity per stage for FAPC can be as low as the matched filter. One embodiment of FAPC is extremely robust to Doppler mismatch which results from illumination of high speed targets.