A novel target detection approach based on adaptive radar waveform design

AbstractTo resolve problems of complicated clutter, fast-varying scenes, and low signal-clutter-ratio (SCR) in application of target detection on sea for space-based radar (SBR), a target detection approach based on adaptive waveform design is proposed in this paper. Firstly, complicated sea clutter is modeled as compound Gaussian process, and a target is modeled as some scatterers with Gaussian reflectivity. Secondly, every dwell duration of radar is divided into several sub-dwells. Regular linear frequency modulated pulses are transmitted at Sub-dwell 1, and the received signal at this sub-dwell is used to estimate clutter covariance matrices and pre-detection. Estimated matrices are updated at every following sub-dwell by multiple particle filtering to cope with fast-varying clutter scenes of SBR. Furthermore, waveform of every following sub-dwell is designed adaptively according to mean square optimization technique. Finally, principal component analysis and generalized likelihood ratio test is used for mitigation of colored interference and property of constant false alarm rate, respectively. Simulation results show that, considering configuration of SBR and condition of complicated clutter, 9 dB is reduced for SCR which reliable detection requires by this target detection approach. Therefore, the work in this paper can markedly improve radar detection performance for weak targets

Performance analysis of quantum-enabled radar systems through modelling and experimentation

This thesis presents the first realisation of a quantum-enabled radar in simulation. The thesis is focused on the fundamental limitations of conventional oscillator phase noise in the performance of radar systems and the development of a quantum-enabled radar (with ultra-low phase noise quantum oscillators) in the simulation. A radar model was developed and validated with the results from a commercially available L-band staring radar at the University of Birmingham to study the effects of oscillator phase noise and the performance capabilities of quantum-enabled radar systems. The whole radar model represents the behaviour of all the fundamental hardware building blocks with reasonable simplifications. The phase noise spectrum of the microwave generator unit locked to its cavity-stabilised internal laser, referred to as one manifestation of the quantum oscillator, is shown to have values at least 20 dB lower for every offset frequency in comparison to the L-band staring radar at the transmit frequency. The conventional oscillator phase noise of the L-band staring radar is shown to manifest as clutter-induced phase noise floor in the range-Doppler plots, with the phase noise floor at least 25 dB above the thermal noise floor, limiting the SNR available for target detection. In range-Doppler plots, the thermal noise floor is the uniform noise floor present in all the range bins, whereas the phase noise floor is the extra noise floor present in range bins with higher clutter power. In comparison to the conventional radar phase noise floor, the quantum-enabled radar simulations show around 20 dB reduction in the phase noise floor in range bins with high levels of clutter in the simulation environment. The detection plots show the successful detection of low RCS targets with quantum-enabled radar that fail to get detected in the classical radar for the same simulation environment. The quantum-enabled radar with ultra-low phase noise quantum oscillators makes it a promising system capable of detecting slow-moving very-low RCS targets even in extreme clutter