Cognitive software defined radar: waveform design for clutter and interference suppression

Abstract

Clutter and radio frequency interference (RFI) are prevalent issues in the field of radar and are specifically of interest to of cognitive radar. Here, methods for applying and testing the utility of cognitive radar for clutter and RFI mitigation are explored. Using the adaptable transmit capability, environmental database, and general “awareness” of a cognitive radar system (i.e. spectrum sensing, geographical location, etc.), a matched waveform is synthesized that improves the signal-to-clutter ratio (SCR), assuming at least an estimate of the target response and the environmental clutter response are known a prior i. RFI may also be mitigated by sensing the RF spectrum and adapting the transmit center frequency and bandwidth using methods that optimize bandwidth and signal-to-interference plus noise ratio (SINR) (i.e. the spectrum sensing, multi-objective (SS-MO) algorithm). The improvement is shown by a decrease in the noise floor. The above methods’ effectiveness are examined via a test-bed developed around a software defined radio (SDR). Testing and the general use of commercial off the shelf (COTS) devices are desirable for their cost effectiveness, general ease of use, as well as technical and community support, but these devices provide design challenges in order to be effective. The universal software radio peripheral (USRP) X310 SDR is a relatively cheap and portable device that has all the system components of a basic cognitive radar. Design challenges of the SDR include phase coherency between channels, bandwidth limitations, dynamic range, and speed of computation and data communication / recording.