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Distributed radars have the potential to combine coherently for achieving a high signal-to-noise ratio (SNR) while maintaining a moderate antenna size. The key to coherently combining multiple radars is obtaining accurate coherent parameters (CPs), which are used to adjust the transmitting/receiving time and phase of each radar. One approach for CP estimation is to transmit orthogonal waveforms. However, ideally, orthogonal waveforms occupying the same frequency band may not be found in practice. Cross-correlation energy leakage exists between non-orthogonal waveforms, which seriously impairs the accurate acquisition of CPs. To solve this problem, we propose a clean signal reconstruction approach for CP estimation. This approach reconstructs clean echoes by gradually stripping out the cross-correlation energy leakage with a reconstruction-elimination-reconstruction framework. And CPs are obtained from these reconstructed clean echoes. Since the majority of cross-correction energy leakages are eliminated, enhanced CP estimation performance can be achieved. Verified simulations are designed for a dual radar scenario. Results show that the proposed approach significantly improves the performance of CP estimation while reducing the SNR requirement for coherently combining multiple radars.

Corona discharges are usually generated at sharp points, edges or on thin wires where the electric field is strongly concentrated. With the rapid development of extra and ultra high-voltage transmission lines, the air corona discharge becomes one of the critical problems associated with high-voltage lines, which can lead to the deterioration of insulation systems, power loss, radio noise. Corona discharge studies have been undertaken for many years, not only because of the scientific interest in the corona mechanism but also because of its practical engineering importance. Transient space charge distribution effect that is one of the important canses in the process of corona discharge, is closely related to the corona discharge mechanism and onset, self-sustaining. In this paper, we present an improved self-consistent, multi-component and two-dimensional plasma hybrid model for simulating the DC positive corona discharge under atmospheric environment. The model is based on the plasma hydrodynamics and the chemical dynamics, and it includes 12 species and 27 reactions. Besides, the photoionization effect is also considered in the proposed model. The simulation and the experiment on bar-plate electrode configuration with an inter-electrode gap of 5.0 mm at 2-5.5 kV are carried out. The discharge voltage-current characteristics and single pulse waveform are in good agreement with the experimental measurements. Based on this model, the electric field distribution, the electron temperature distribution, and the evolution of charged species distribution are investigated in detail. The results show that distributions of electron temperature and electric field have the same patterns, In the process of discharge, electron density is kept at 1019 m-3 or so. O4+ is dominant compared with the other charged heavy species, and O2+ and N2+ play the key role in secondary electron emission: the unmbers of O2- and O are the largest in negative ions and neutral particle respectively, they play a negligible role in discharge process.

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