Cong Li's research while affiliated with China Academy of Space Technology (CAST) and other places

In this study, ZnFe2O4 pleated hollow microspheres were synthesized by a one-step chemical vapor deposition (CVD) method using NaCl as a green salt template, and successfully used for the detection of acetone gas. NaCl as a green non-polluting and easy-to-remove structural template effectively modulate the morphology and structure of ZnFe2O4. The prepared sensitive materials were observed by SEM and TEM to have dense solid, hollow, pleated hollow and nanosheet structures, respectively. Among them, ZnFe2O4 pleated hollow microspheres exhibited a large specific surface area (185.24 m²/g) and the best sensing performance. Compared with other materials, ZnFe2O4 pleated hollow microspheres presented a response of up to 95.0 for 100 ppm acetone at the optimal working temperature of 200 °C. The large specific surface area and superior surface permeability exhibited by the pleated hollow structure effectively increased the reaction sites and overall utilization of the sensitive material both internally and externally, which resulted in ultra-high response properties to acetone. The ZnFe2O4 pleated hollow microspheres prepared using NaCl green template had excellent acetone molecular sensitivity properties, which is expected to be a promising sensitive material for acetone gas sensors.

Unmanned aerial vehicle (UAV) multi-hop communication networks are foreseen to be widely employed in both military and civilian scenarios. However, in ultra-dense scenarios with swarm UAVs, nodes are highly dynamic mobile, ultra-dense deployment and non-centralized distribution. These characteristics make the centralized resource management policy not apply. Meanwhile, existing routing protocols can't meet the performance challenges of high dynamic, topology and link frequency changes of ultra-dense scenarios with swarm UAVs. To solve the above challenges of resource management and routing protocol, a cross-layer optimization method is presented with a novel mean field game (MFG) in this paper. It is based on the cross-layer design method of the MFG theory and jointly considers the power resources in the physical layer, frequency resources in the medium access control (MAC) layer, and routing resources in the network layer. By dividing into subproblems, the original problem is solved. Meanwhile, the optimal data transmission path can be selected through the management and allocation of frequency resources and power resources. A crosslayer resource management dynamic source routing (CLRMDSR) protocol is designed based on that which adds link quality measurement. The simulation results show that the presented CLRM-DSR with the proposed resource management scheme can improve the data packet transmission rate, reduce end-toend delay, and lower routing overhead for the multi-hop swarm UAV communication network.

The smooth variable structure filter (SVSF) is a new-type filter based on the sliding-mode concepts and has good stability and robustness in overcoming the modeling uncertainties and errors. However, SVSF is insufficient to suppress Gaussian noise. A novel smooth variable structure smoother (SVSS) based on SVSF is presented here, which mainly focuses on this drawback and improves the SVSF estimation accuracy of the system. The estimation of the linear Gaussian system state based on SVSS is divided into two steps: Firstly, the SVSF state estimate and covariance are computed during the forward pass in time. Then, the smoothed state estimate is computed during the backward pass by using the innovation of the measured values and covariance estimate matrix. According to the simulation results with respect to the maneuvering target tracking, SVSS has a better performance compared with another smoother based on SVSF and the Kalman smoother in different tracking scenarios. Therefore, the SVSS proposed in this paper could be widely applied in the field of state estimation in dynamic system.

Model training is a key technique for radar target recognition. Traditional model training algorithms in the framework of single task leaning ignore the relationships among multiple tasks, which degrades the recognition performance. In this paper, we propose a clustered multi-task learning, which can reveal and share the multi-task relationships for radar target recognition. To further make full use of these relationships, the latent multi-task relationships in the projection space are taken into consideration. Specifically, a constraint term in the projection space is proposed, the main idea of which is that multiple tasks within a close cluster should be close to each other in the projection space. In the proposed method, the cluster structures and multi-task relationships can be autonomously learned and utilized in both of the original and projected space. In view of the nonlinear characteristics of radar targets, the proposed method is extended to a non-linear kernel version and the corresponding non-linear multi-task solving method is proposed. Comprehensive experimental studies on simulated high-resolution range profile dataset and MSTAR SAR public database verify the superiority of the proposed method to some related algorithms.

Based on the orthogonal frequency division multiplexing (OFDM) technique, an intelligent waveform is designed, which is suitable for simultaneously performing data transmission and radar sensing. In view of the inherent high peak-to-mean envelope power ratio (PMERP) and poor peak-to-side-lobe ratio (PSLR) problems in the OFDM based radar and communication (RadCom) waveform design, we propose two technologies to deal with that. To be specific, we adopt Gray code technology to reduce the PMERP and simultaneously choose an optimal cyclic sequence to improve the PSLR of RadCom waveform. In our method, the optimal cyclic sequence is dynamically generated to continuously provide the best waveform according to the change of communication data. In addition, to meet the requirements of different radar detection tasks, two simple methods are utilized to adjust the bandwidth of RadCom waveform. To verify the advantages of the designed waveform, we conduct several simulation experiments to compare with some existing RadCom waveforms. The results show that our designed RadCom waveform can simultaneously achieve lower PMERP and higher PSLR. In addition, our designed RadCom waveform has a thumbtack type fuzzy function and shows the good ability to do multitarget detection.

Extended target detection in the presence of K-distributed clutter has gained a special interest in recent years. High-resolution radars allow a target to be found in several resolution cells. Therefore, the detection rate and the false alarm rate of an extended target should be analyzed by these cells jointly rather than in one single resolution cell. A detector in which all the cells whose magnitude affected by one target are considered jointly is present. The performance and optimal parameters of the detector are analyzed in detail. Meanwhile, the large amount of calculation caused by enormous raw data is also considered. Then, an efficient method based on region growing algorithm and contour tracking algorithm is proposed. Only part of the resolution cells is scanned once with the proposed method, while all the cells are scanned at least one times in the existing methods. Therefore, considerable calculations are saved. Furthermore, the proposed method and several existing methods are performed with real data and simulated data, and the results show that the proposed model is practical and efficient to detect the extended targets in K-distributed clutters.

The detection of randomly distributed extended multi-targets under various circumstances is of special interest. An improved plot fusion method is proposed in this work. The proposed plot fusion method is based on a multi-contour tracking and region growing algorithm. The proposed method is applied to the DP-TBD algorithm for extended targets in the K-distributed sea clutter. Models and shortcomings of existing methods are presented. The principle of the DP-TBD algorithm for extended targets and implementation of the improved plot fusion method are explained in detail. In the simulation, the methods are applied to almost all situations, close trajectories, crossing trajectories, small targets, weak targets and targets in a high clutter region. Comparison with existing methods demonstrates that the proposed method is practical and superior to the existing methods.

X-ray pulsars offer stable, periodic X-ray pulse sequences that can be used in spacecraft positioning systems. A method using X-ray pulsars to determine the initial orbit of a satellite is presented in this paper. This method suggests only one detector to be equipped on the satellite and assumes that the detector observes three pulsars in turn. To improve the performance, the use of incremental phase in one observation duration is proposed, and the incremental phase is combined with the time difference of arrival (TDOA). Then, a weighted least squares (WLS) algorithm is formulated to calculate the initial orbit. Numerical simulations are performed to assess the proposed orbit determination method.