Huijie Liu

In this article, the problem of simultaneously estimating and localizing multiple-input multiple-output (MIMO) radar emitters is considered for a distributed multi-station passive localization system, wherein the transmitted signal is unknown for receiver stations. To achieve highly accurate and robust localization performance, a novel algorithm based on the direct position determination (DPD) algorithm, Karhunen–Loève (KL) transform, and feature matching (FM) is addressed to jointly estimate the emitter position and the unknown signal waveform. First, we further derive the objective function of the DPD method and present an enhanced strategy to exploit as much waveform information as possible without any prior knowledge. By applying KL transform and FM techniques, the proposed method achieves MIMO radar emitter identification and emitter localization. The numerical results show that the proposed algorithm outperforms the existing DPD approaches which ignore the transmitted signals, especially for a low signal-to-noise ratio (SNR).

Unlike phased array, frequency diverse array (FDA) applies a tiny frequency offset across the antenna elements to generate a range-angle-dependent beampattern. However, due to the range-angle coupling property, the emitter position cannot be obtained directly from conventional FDA beamforming peaks. This paper proposes a novel passive localization approach based on direction modulation (DM) and Chan algorithm. By applying DM, the angle-range coupling can be wiped off well, which has a significant influence on the emitter localization. Simulation results are implemented to verify the validity and superiority of the proposed technique.

Low earth orbit (LEO) satellite networks can provide Internet service to users in areas where cellular networks are difficult to deploy. One critical function of satellites is to transfer data from satellite networks to ground core network through earth stations (ESs). The Ka-band multiple-input multiple-output (MIMO) can be used to establish feeder links with larger bandwidth between satellites and ESs. However, propagation at the Ka band is subjected to rain attenuation and various atmospheric fading mechanisms, which severely reduce the maximum link capacity. As a result, the insufficient capacity of feed link becomes the throughput bottleneck of satellite networks. In order to increase network throughput, it is important to fully use feeder link resources. In this paper, we propose a cooperation scheme to route packets to ESs through a well-resourced feeder link, such that the bandwidth of the feeder links can be fully utilized and the throughput of data downloading at the ESs is maximized. Firstly, we model the satellite network system and the feeder link based on MIMO technology. Then, a Maximum-Flow-Minimum-Cost (MCMF) routing algorithm consisting of two Linear Programs (LPs) is presented to compute maximum-flow routings for data download. Eventually, a variety of simulations are conducted to assess the proposed scheme, which shows that the cooperative routing scheme outperforms the existing SiRRS method in terms of throughput and delay.

In this work, the comprehensive influence of different reflector subtended angle values and the displacement of feed on a parabolic reflector antenna was studied. There are two main reasons for this research; one is that the actual performance of antennas is worse than indicated in theoretical analysis, and the other is that the deep or derived impacts of some deviations cannot be taken into sufficient account for antenna design. Differing from the ideal theoretical analysis and calculation, a parabolic reflector antenna with a pyramidal horn feed was designed to make the antenna design more suitable for the actual project. The performance of the antenna with different deviations of the feed under different reflector subtended angles was then given. This research has higher practical guiding significance in terms of margin consideration for the design of antennas in engineering.

For the purpose of simultaneously estimating and locating the linear frequency modulation (LFM) emitter with unknown parameters, an innovative approach, i.e., Fast Direct Position Determination (FDPD), is introduced. The proposed algorithm is based on maximum likelihood estimation (MLE) and spectrum detection. To improve the accuracy and overcome the dramatic complexity of plain maximum likelihood formulation, we further derive the objective function equation of Direct Position Determination (DPD) algorithm and present an enhanced strategy to solve the highly nonlinear optimization problem. By combining the two-step localization method, one-step localization method, and short-time Fourier transform (STFT), our approach realizes jointly estimation of the transmitted signal parameters and emitter localization. Simulation results show that the proposed method is superior compared to the existing DPD, and two-step localization algorithms in terms of localization error and computational complexity, especially for low signal-to-noise ratio (SNR).

This work investigates the effects of the surface errors of the satellite antenna on the detection performance of the space VLBI system. First, the relationship between the surface errors and the antenna gain loss is analyzed, and then the influence of the gain loss on the detection performance of the VLBI system is analyzed. Both the uniform and nonuniform distributions of errors are studied, and the second-order Taylor expansion is performed on the errors to simplify the calculation. When the errors distribute nonuniformly, the solver SCIP is adopted to solve the corresponding distribution, which leads to the maximum gain loss of the antenna. Taking the VLBI system with two base stations as the object, and each station’s radio telescope is a hoop truss deployable antenna with 30 m aperture, the effects of antenna gain loss on the detection capability of the radio telescope and the delay error of the VLBI system are studied. The study of extreme working conditions will have a higher guiding significance for the overall link analysis of practical projects.

This paper investigates the robust relay beamforming design for the multiantenna nonregenerative cognitive relay networks (CRNs). Firstly, it is proved that the optimal beamforming matrix could be simplified as the product of a variable vector and the conjugate transposition of a known channel response vector. Then, by exploiting the optimal beamforming matrix with simplified structure, an improved robust beamforming design is proposed. Analysis and simulation results show that, compared with the existing suboptimal scheme, the proposed method can achieve higher worst-case channel capacity with lower computational complexity.