Hai Deng

Polyphase code design for Orthogonal Netted Radar systems

Orthogonal netted radar systems (ONRS) can fundamentally improve radar performance by using a group of specially designed orthogonal signals. A novel hybrid algorithm is proposed to numerically optimize such orthogonal polyphase code sets. The proposed algorithm integrates a statistical simulated annealing algorithm with the traditional iterative code selection method and is demonstrated to be effective for the design of polyphase signals used in ONRS. Some of the design results are presented and discussed. The effect of Doppler frequency shift on the performance of the designed signals is also investigated.

Discrete frequency-coding waveform design for netted radar systems

A novel method is proposed to design discrete frequency-coding waveforms (DFCWs) for the netted radar systems. Some of the designed results are presented and they indicate that the proposed algorithm is effective for the DFCW design.

Effective CLEAN algorithms for performance-enhanced detection of binary coding radar signals

With binary coding waveform as radar pulse compression signal, the sidelobe of the matched processing result of the received signals is a serious interference to the effective detection of multiple targets. In this paper, the CLEAN algorithms are introduced to eliminate such sidelobes and significantly improve the target detection performance of binary coding radar signals. A novel modified CLEAN algorithm is proposed to remove the sidelobe interferences in formulating target range profile when wideband binary coding signals are used. The effectiveness of the CLEAN algorithms is demonstrated through the processing results.

Fast solution of electromagnetic integral equations using adaptive wavelet packet transform

The adaptive wavelet packet transform is applied to sparsify the moment matrices for the fast solution of electromagnetic integral equations. In the algorithm, a cost function is employed to adaptively select the optimal wavelet packet expansion/testing functions to achieve the maximum sparsity possible in the resulting transformed system. The search for the best wavelet packet basis and the moment matrix transformation are implemented by repeated two-channel filtering of the original moment matrix with a pair of quadrature filters. It is found that the sparsified matrix has above-threshold elements that grow only as O(N/sup 1.4/) for typical scatterers. Consequently the operations to solve the transformed moment equation using the conjugate gradient method scales as O(N/sup 1.4/). The additional computational cost for carrying out the adaptive wavelet packet transform is evaluated and discussed.

Orthogonal netted radar systems

An ONRS is a radar networking system consisting of multiple pulse compression radars with each transmitting a distinct coding signal exclusively from a group of orthogonal coding waveforms and equipped with a bank of parallel matched filters. The fundamental difference between ONRS and traditional netted radar systems is that ONRS is capable of operating as monostatic radars and multistatic radars simultaneously, to maximally increase the number of target echoes and thus to achieve much better radar performance through target information fusion processing. It has been further illustrated that the application of ONRS will not only significantly improve radar performance in target detection, measurement, and recognition, but also greatly enhance radar capabilities in countering anti-radar techniques such as ARM, high-speed highly-maneuvering targets, stealth targets, and electronic countermeasures. The key technologies and challenges for implementing ONRS have been identified as orthogonal coding signal design, interference rejection, overcoming Doppler shift effect, improving search efficiency, and optimizing ONRS configuration. An ONRS can be conveniently constructed from multiple slightly-modified monostatic radars, which renders the real-time formulation of m Ad-Hoc ONRS possible. Because ONRS is structurally compatible with traditional monostatic radar and have the potential to significantly improve radar performance, we expect that ONRS will become one of the most important forms of radar sensor in the near future.

Adaptive Radar Beamforming for Interference Mitigation in Radar-Wireless Spectrum Sharing

The key to the feasibility of spectrum sharing between radar and wireless systems is effective mainlobe interference mitigation processing by the radar. Traditional array processing is capable to cancel sidelobe interferences only. This letter presents an innovative beamforming approach, the first of its kind, to eliminate wireless interference in both mainlobe and sidelobe directions based on a coherent phase-coding multiple-input multiple-output (MIMO) radar platform. The theoretical proof and conditions of simultaneous mainlobe interference cancellation and target detection using coherent MIMO radar are mathematically derived and numerically verified. The simulation results demonstrate the radar can effectively eliminate wireless interferences from base stations and mobile handsets during spectrum-sharing.

A Virtual Antenna Beamforming (VAB) Approach for Radar Systems by Using Orthogonal Coding Waveforms

An innovative approach is introduced to form virtual transmitting and receiving radar antenna beams simultaneously by transmitting orthogonal coding waveforms from the antenna elements and digitally processing of their echoes at the receiver. Multiple virtual transmitting-receiving beams can be formed simultaneously by employing an equal number of beamforming filters without increasing transmitting power or antenna gain or resolution loss. The virtually formed antenna beams can provide equivalent antenna gains and spatial resolutions as the conventional phased arrays of the same size. Because the actual antenna radiation pattern can be made almost isotropic, the new system has low probability of intercept (LPI) property. With both transmitting and receiving beams virtually implemented through digital filtering, costly radiation phase shift used in phased arrays is not needed for beam scanning in the proposed system.

Waveform Optimization for Transmit Beamforming With MIMO Radar Antenna Arrays

For coherent MIMO radar the optimal target signal processing can be achieved for any transmitted waveforms or radiation beam pattern, making transmit beamforming through waveform design possible without degrading target detection performance. In this work, an innovative waveform optimization approach termed phase-only variable metric method (POVMM) is proposed for coherent MIMO radar waveform design to form a desired transmit beam pattern such as one with radiation nulls in certain directions. The waveform design is carried out by minimizing the radiation powers of the MIMO radar antenna in the selected directions with optimization variables constrained to the waveform phases only. The gradient function of the cost function with regard to waveform phases is analytically derived for the optimization and the POVMM is developed based on the variable metric methods with a flexible search step sizing strategy for improving optimization efficiency. The proposed approach is validated with various designs and simulations.

An efficient wavelet preconditioner for iterative solution of three-dimensional electromagnetic integral equations

A wavelet-based preconditioning method is proposed to facilitate the iterative solution of three-dimensional (3-D) electromagnetic integral equations. The preconditioner is derived from the wavelet transform of the moment matrix. It is based on the observation that both the moment matrix and its inverse exhibit a sparse, multilevel finger structure. A method based on the Forbenius-norm minimization is used to solve the inverse of the matrix under the multilevel finger structure. Numerical results on a 3-D cavity show that the iteration numbers are significantly reduced with the wavelet-preconditioned system. The computational cost of the preconditioner is kept under O(NlogN).

Image feature-based space-time processing for ground moving target detection

An image feature-based space time processing (IFSTP) algorithm is introduced to effectively detect ground moving targets in clutter and jamming via airborne radar. This new approach exploits the distinct image features of targets and interference signals in the angle-Doppler domain. An image segmentation algorithm, referred to as region growing, extracts targets and interference features in the angle-Doppler domain, and an innovative block-size detection algorithm discriminates between moving targets and interference based on the extracted image features. The proposed IFSTP algorithm is particularly suitable for detecting ground moving targets in highly nonhomogeneous clutter environments, without any requirement for clutter covariance estimation.