The combination of a multihop relay system and orthogonal frequency-division multiplexing (OFDM) modulation is a promising way to increase the capacity and coverage area. For the OFDM two-hop relay system with separate power constraints, joint subcarrier matching and power allocation is considered in this paper, which uses the “decode-and-forward” relay strategy. The aforementioned problem can be formulated as a mixed binary integer programming problem, which is prohibitive when trying to find the global optimum. By separating the subcarrier matching and the power allocation, the optimal scheme, i.e., the optimal joint subcarrier matching and power allocation, is presented in this paper. After that, a suboptimal scheme with less complexity is also proposed, which can also be used to better understand the effects of power allocation. Simulation results show that the capacity of the optimal scheme is almost equivalent to the upper bound of thesystem capacity, and the capacity of the suboptimal scheme is close to that of the optimal scheme. In addition, simulation results also show that the one-to-one subcarrier matching is almost optimal, although it simplifies the system architecture.

In this article, we propose a method to estimate the synthetic aperture radar interferometry (InSAR) interferometric phase based on the model of correlation weight joint pixel by using the joint subspace projection technique. In the method, the correlation weight joint data vector is constructed and the data vector can make the noise subspace dimension of the corresponding weight covariance matrix which is not affected by the coregistration error, thus avoiding the trouble of calculating the noise subspace dimension before estimating the InSAR interferometric phase. The method takes advantage of the coherence information of neighboring pixel pairs to auto-coregister the SAR images and employs the projection of the joint signal subspace onto the corresponding joint noise subspace to estimate the terrain interferometric phase. The method can auto-coregister the SAR images and reduce the interferometric phase noise simultaneously. Theoretical analysis and computer simulation results show that the method can provide accurate estimate of the interferometric phase (interferogram) even when the coregistration error reaches one pixel. The effectiveness of the method is verified via simulated data and real data.

In recent years, ground moving target imaging in synthetic aperture radar (SAR) has attracted the attention of many researchers all over the world. A novel approach is proposed for the ground moving target imaging and motion parameter estimation using single channel SAR. First, a second-order generalised keystone formatting method is used to compensate for the range curvature. Secondly, the estimated slope of the target echo’s envelope is used for the range walk compensation. Thirdly, Doppler parameters of moving targets obtained via spectral analysis are used for the imaging and positioning of ground moving targets. Finally, motion parameters of moving targets can be estimated on the basis of the relationship between Doppler and motion parameters. Both numerical and experimental results are provided to demonstrate the performance of the proposed approach.

High range resolution (HRR) moving target indicator (MTI) is becoming increasingly important for many military and dvilian applications such as the detection and dassification of moving targets in strong clutter background. We consider the problem of extracting the HRR features of moving targets with very dosely spaced scatterers in the presence of strong stationary clutter, where the range migration and Vopplel\"frequency are taken into account. A relaxation-based algorithm，which is robust and computationally simple, is propOsed to deal with the above problem. Numerical results have shown that the proposed algorithm exhibits super resolution and excellent estimation performance.

A new algorithm, referred to as the SPAR (Semiparametric) algorithm, is presented herein for target feature extraction and complex image formation via synthetic aperture radar (SAR). The algorithm is based on a fiexible data model that models each target scatterer as a two-dimensional (2-D) complex sinusoid with arbitrary unknown amplitude and constant phase in cross-range and with constant amplitude and phase in range. By attempting to deal with one corner reflector, such as one dihedral or trihedral, at a time, the algorithm can be used to effectively mitigate the artifacts in the SAR images due to the flexible data model. Another advantage of SPAR is that it can be used to obtain initial conditions needed by other parametric target feature extraction methods to reduce the total amount of computations needed. Both numerical and experimental examples are provided to demonstrate the performance of the proposed algorithm.