How to Select the Best Sensors for TDOA and TDOA/AOA Localization?

This paper focuses on the sensor subset optimization problem in time difference of arrival(TDOA) passive localization scenario. We seek for the best sensor combination by formulating a non-convex optimization problem, which is to minimize the trace of covariance matrix of localization error under the condition that the number of selected sensors is given. The accuracy metric is described by the localization error covariance matrix of classical closed-form solution, which is introduced to convert the TDOA nonlinear equations into pseudo linear equations. The non-convex optimization problem is relaxed to a standard semi-definite program(SDP) and efficiently solved in a short time. In addition, we extend the sensor selection method to a mixed TDOA and angle of arrival(AOA) localization scenario with the presence of sensor position errors. Simulation results validate that the performance of the proposed sensor selection method is very close to the exhaustive search method.

Waveform design for radar and extended target in the environment of electronic warfare

Transmit waveform optimization is critical to radar system performance. There have been a fruit of achievements about waveform design in recent years. However, most of the existing methods are based on the assumption that radar is smart and the target is dumb, which is not always reasonable in the modern electronic warfare. This paper focuses on the waveform design for radar and the extended target in the environment of electronic warfare. Three different countermeasure models between smart radar and dumb target, smart target and dumb radar, smart radar and smart target are proposed. Taking the signal-to-interferenceplus-noise ratio(SINR) as the metric, optimized waveforms for the first two scenarios are achieved by the general water-filling method in the presence of clutter. For the last case, the equilibrium between smart radar and smart target in the presence of clutter is given mathematically and the optimized solution is achieved through a novel two-step water-filling method on the basis of minmax theory. Simulation results under different power constraints show the power allocation strategies of radar and target and the output SINRs are analyzed.

Effect of Facet Displacement on Radiation Field and Its Application for Panel Adjustment of Large Reflector Antenna

Large reflector antennas are widely used in radars, satellite communication, radio astronomy, and so on. The rapid developments in these fields have created demands for development of better performance and higher surface accuracy. However, low accuracy and low effi- ciency are the common disadvantages for traditional panel alignment and adjustment. In order to improve the surface accuracy of large reflector antenna, a new method is pre- sented to determinate panel adjustment values from far field pattern. Based on the method of Physical Optics （PO）, the effect of panel facet displacement on radiation field value is derived. Then the linear system is constructed between panel adjustment vector and far field pattern. Using the method of Singular Value Decomposition （SVD）, the adjustment value for all panel adjustors are obtained by solving the linear equations. An experiment is conducted on a 3.7 m reflector antenna with 12 segmented panels. The results of simulation and test are similar, which shows that the presented method is feasible. Moreover, thediscussion about validation shows that the method can be used for many cases of reflector shape. The proposed research provides the instruction to adjust surface panels efficiently and accurately.

Reflection and transmission of Laguerre Gaussian beam from uniaxial anisotropic multilayered media

Based on angular spectrum expansion and 4 × 4 matrix theory, the reflection and transmission characteristics of a Laguerre Gaussian （LG） beam from uniaxial anisotropic multilayered media are studied. The reflected and transmitted beam fields of an LG beam are derived. In the case where the principal coordinates of the uniaxial anisotropic media coincide with the global coordinates, the reflected and transmitted beam intensities from a uniaxial anisotropic slab and three-layered media are numerically simulated. It is shown that the reflected intensity components of the incident beam, especially the TM polarized incident beam, are smaller than the transmitted intensity components. The distortion of the reflected intensity component is more evident than that of the transmitted intensity component. The distortion of intensity distribution is greatly affected by the dielectric tensor and the thickness of anisotropic media. We finally extend the application of the method to general anisotropic multilayered media.

RFD-Rao and RFD-Wald tests for distributed targets with range walking effect

提出两种新型自适应分布式目标检测器:距离频域Rao(RFD-Rao)和距离频域Wald(RFD-Wald)检测器。该方法考虑相参处理间隔(CPI)内部分均匀干扰环境和目标距离走动效应的影响,分析检测器的渐近性能,并给出不同杂波协方差矩阵和功率水平下的恒虚警率(CFAR)特性分析。将本文所提出的自适应检测器的性能通过蒙特卡罗试验进行了验证,仿真结果证明所提出的检测算法与现有的类似检测器相比的有效性。

Numerical Evaluation of Effect of Motion of Samples on Ptychographic Imaging and Solution with a Random Phase Modulator

The retrieval of ptychographical imaging encounters a degradation produced by motion of samples. The mech- anism of capturing the diffractive patterns of a sample which is motile is simulated numerically. The relation between the retrieval degradation and the amplitude of motion is evaluated quantitatively. Experiments indicate that the reliability and resolution of the complex amplitude retrieval of a sample is inversely proportional to its vibratory amplitude. A random phase modulated aperture is employed to cure the degradation produced by the motion of samples to a certain extent.

Wideband MIMO Radar Waveform Optimization Based on Range Profile

Aiming at the signal bandwidth design problem for multi-target imaging task,a kind of multiple input multiple output(MIMO)radar waveform design method is proposed.At first,the closed-loop feedback between the range profile and the signal bandwidth,which can design the minimum bandwidth of a transmitting signal that can distinguish each scatterer of the target in range direction,is established.Then,considering the request of beam pattern and the bandwidth limitation,a waveform optimization model is established and solved.Therefore,the multi-target observation and the dynamic adjustment of the signal bandwidth are accomplished.In the end,the simulation results prove the performance of the algorithm in a low SNR circumstance.

Dynamic Spectrum Control-Assisted Secure and Efficient Transmission Scheme in Heterogeneous Cellular Networks

Heterogeneous cellular networks(HCNs)are envisioned as a promising architecture to provide seamless wireless coverage and increase network capacity.However,the densified multi-tier network architecture introduces excessive intra-and cross-tier interference and makes HCNs vulnerable to eavesdropping attacks.In this article,a dynamic spectrum control(DSC)-assisted transmission scheme is proposed for HCNs to strengthen network security and increase the network capacity.Specifically,the proposed DSC-assisted transmission scheme leverages the idea of block cryptography to generate sequence families,which represent the transmission decisions,by performing iterative and orthogonal sequence transformations.Based on the sequence families,multiple users can dynamically occupy different frequency slots for data transmission simultaneously.In addition,the collision probability of the data transmission is analyzed,which results in closed-form expressions of the reliable transmission probability and the secrecy probability.Then,the upper and lower bounds of network capacity are further derived with given requirements on the reliable and secure transmission probabilities.Simulation results demonstrate that the proposed DSC-assisted scheme can outperform the benchmark scheme in terms of security performance.Finally,the impacts of key factors in the proposed DSC-assisted scheme on the network capacity and security are evaluated and discussed.

New hybrid FDTD algorithm for electromagnetic problem analysis

Since the time step of the traditional finite-difference time-domain(FDTD) method is limited by the small grid size, it is inefficient when dealing with the electromagnetic problems of multi-scale structures.Therefore, the explicit and unconditionally stable FDTD(US-FDTD) approach has been developed to break through the limitation of Courant–Friedrich–Levy(CFL) condition.However, the eigenvalues and eigenvectors of the system matrix must be calculated before the time iteration in the explicit US-FDTD.Moreover, the eigenvalue decomposition is also time consuming, especially for complex electromagnetic problems in practical application.In addition, compared with the traditional FDTD method, the explicit US-FDTD method is more difficult to introduce the absorbing boundary and plane wave.To solve the drawbacks of the traditional FDTD and the explicit US-FDTD, a new hybrid FDTD algorithm is proposed in this paper.This combines the explicit US-FDTD with the traditional FDTD, which not only overcomes the limitation of CFL condition but also reduces the system matrix dimension, and introduces the plane wave and the perfectly matched layer(PML) absorption boundary conveniently.With the hybrid algorithm, the calculation of the eigenvalues is only required in the fine mesh region and adjacent coarse mesh region.Therefore, the calculation efficiency is greatly enhanced.Furthermore, the plane wave and the absorption boundary introduction of the traditional FDTD method can be directly utilized.Numerical results demonstrate the effectiveness, accuracy, stability, and convenience of this hybrid algorithm.

Source Recovery in Underdetermined Blind Source Separation Based on Artificial Neural Network

We propose a novel source recovery algorithm for underdetermined blind source separation, which can result in better accuracy and lower computational cost. On the basis of the model of underdetermined blind source separation, the artificial neural network with single-layer perceptron is introduced into the proposed algorithm. Source signals are regarded as the weight vector of single-layer perceptron, and approximate ι~0-norm is taken into account for output error decision rule of the perceptron, which leads to the sparse recovery. Then the procedure of source recovery is adjusting the weight vector of the perceptron. What's more, the optimal learning factor is calculated and a descent sequence of smoothed parameter is used during iteration, which improves the performance and significantly decreases computational complexity of the proposed algorithm. The simulation results reveal that the algorithm proposed can recover the source signal with high precision, while it requires lower computational cost.

Bistable Stochastic Resonance Enhanced 4-ary PAM Signal Detection under Low SNR

To boost the performance of 4-ary pulse amplitude modulated(PAM) at low signal-to-noise ratio(SNR), bistable stochastic resonance(BSR) system is introduced into digital communications system and get a reliable signal detection scheme. In this paper, we first analyse BSR system for different amplitudes of 4-ary PAM signals. The steadystate of the bistable system will be statistically distinct, and the feasibility of the proposed detection scheme is confirmed. On this basis, we present a detailed study on steady-state transitions of the BSR system, and an explicit expression of the bistable system parameters is derived. By setting the bistable system parameters, bistable system, 4-ary PAM signal, and noise reach the resonance state, and the BSR-based detection scheme is implemented. Moreover, we derive an analytical expression to calculate the symbol error rate(SER) of 4-ary PAM signals with the BSR-based detection under additive white Gaussian noise(AWGN). Finally, the simulation results validate that BSR-based detection scheme can improve the detection performance while efficiently reducing the symbol error rate.

Direction-of-arrival estimation for uniform circular arrays under small sample size

With a small number of snapshots, performances of uniform circular array (UCA) root-MUSIC based methods for directionof- arrival (DOA) estimation suffer serious degradation, because the beamspace sample covariance matrix (BSCM) severely deviates from the true one. To solve this problem, an iterative technique is proposed. The proposed technique has two key points: transform array data into beamspace data and construct a BSCM; modify the BSCM repeatedly by removing the residual parts. Meanwhile, error and beamspace leakage associated with the BSCM are investigated. The proposed technique can significantly reduce the error and the beamspace leakage which in turn could improve the performance for DOA estimation. Simulation results are given to illustrate the superiority of the proposed technique for uncorrelated and correlated signals. © 2016 Beijing Institute of Aerospace Information.

Fractional Frequency Offset Estimation for OFDM Systems in Non-Cooperative Communication

The traditional fractional frequency offset(FFO) estimation schemes for orthogonal frequency division multiplexing(OFDM) in non-cooperative communication have the problems of susceptible performance with the frequency offset values and the number of OFDM symbols,a novel fractional frequency offset blind estimation scheme based on EKF for OFDM systems is conceived.The nonlinear function of the frequency offset is calculated by employing the correlation.And then the frequency offset is estimated by means of the iterative algorithm of EKF.The finally fractional frequency offset is estimated by adopting repeated the above process.Simulation results demonstrate that the proposed scheme is robust to the frequency offset values without any requirements of a prior knowledge.

Full aperture imaging algorithm for highly squinted TOPS SAR

Aiming at solving the azimuth signal aliasing problem in the Doppler domain, the azimuth time aliasing problem after range cell migration correction (RCMC) and the severe range and the azimuth coupling problem in both the phase and envelope for highly squinted terrain observation by progressive scans (TOPS) synthetic aperture radar (SAR), a novel full aperture imaging algorithm is presented. An unaliased two-dimensional (2-D) spectrum is first obtained by the azimuth preprocessing; the modified range migration algorithm (RMA) is then used to complete RCMC; and finally the azimuth signal is focused in the Doppler domain by spectral analysis (SPECAN) and deramping. Simulations and real data processing results validate the effectiveness of the proposed algorithm. © 2016 Beijing Institute of Aerospace Information.

Object Detection Research of SAR Image Using Improved Faster Region-Based Convolutional Neural Network

Target detection technology of synthetic aperture radar(SAR)imageis widely used in the field of military reconnaissance and surveillance.The traditional SAR image target detection methods need to be provided a lot of empirical knowledge because the characteristics of SAR images in different configurations(attitude,pitch angle,imaging parameters,etc.)will change greatly,resulting in high generalization error.Currently,deep learning method has achieved great success in the field of image processing.Research shows that deep learning can achieve a more intrinsic description of the data,while the model has a stronger ability of modeling and generalization.In order to solve the problem of insufficient data in SAR data sets,an experimental system for acquiring SAR image data in real scenes was built.Then the transfer learning method and the improved convolution neural network algorithm(PCA+Faster R-CNN)are applied to improve the target detection precision.Finally,experimental results demonstrate the significant effectiveness of the proposed method.

Factors influencing electromagnetic scattering from the dielectric periodic surface

The scattering characteristics of the periodic surface of infinite and finite media are investigated in detail.The Fourier expression of the scattering field of the periodic surface is obtained in terms of Huygens’ s principle and Floquet’s theorem.Using the extended boundary condition method(EBCM) and T-matrix method, the scattering amplitude factor is solved,and the correctness of the algorithm is verified by use of the law of conservation of energy.The scattering cross section of the periodic surface in the infinitely long region is derived by improving the scattering cross section of the finite period surface.Furthermore, the effects of the incident wave parameters and the geometric structure parameters on the scattering of the periodic surface are analyzed and discussed.By reasonable approximation, the scattering calculation methods of infinite and finite long surfaces are unified.Besides, numerical results show that the dielectric constant of the periodic dielectric surface has a significant effect on the scattering rate and transmittance.The period and amplitude of the surface determine the number of scattering intensity peaks, and, together with the incident angle, influence the scattering intensity distribution.

Tradeoffs in Covert Wireless Communication with a Controllable Full-Duplex Receiver

This paper investigates the tradeoff of the communication link and the eavesdropping link in covert communication in the presence of a full-duplex(FD)receiver.When a warden(Willie)attempts to detect the signal transmitted from a legitimate transmitter(Alice),the controllable FD receiver(Bob)can transmit with random power to impose interference uncertainty to Willie and force it to make an incorrect decision.To maximize the average transmission rate(ATR)of Alice-Bob and the average covert probability(ACP)for Willie,we propose a multi-objective optimization framework to optimize Bob’s power uncertainty range(PUR)and spatial position jointly,subject to the sufficient condition for covert communication and the none-deployed-zone(NDZ).Due to the presence of multiple optimization objectives and nonconvex constraints,the nondominated sorting genetic algorithm II(NSGA-II)is utilized to explore the Pareto front and to give a set of solutions that reflect tradeoffs between the two conflicting objectives.Simulation results reveal that the solutions determined by the NSGA-II have larger values for both ATR and ACP than the other two baselines.Simulations also show the positive effect of the width of the PUR of Bob on the Pareto front.

A method based on Chinese remainder theorem with all phase DFT for DOA estimation in sparse array

This paper takes further insight into the sparse geometry which offers a larger array aperture than uniform linear array(ULA)with the same number of physical sensors.An efficient method based on closed-form robust Chinese remainder theorem(CFRCRT)is presented to estimate the direction of arrival(DOA)from their wrapped phase with permissible errors.The proposed algorithm has significantly less computational complexity than the searching method while maintaining similar estimation precision.Furthermore,we combine all phase discrete Fourier transfer(APDFT)and the CFRCRT algorithm to achieve a considerably high DOA estimation precision.Both the theoretical analysis and simulation results demonstrate that the proposed algorithm has a higher estimation precision as well as lower computation complexity.

Electromagnetic Scattering of a High-Order Bessel Trigonometric Beam by Typical Particles

The scattering of an electromagnetic high-order Bessel trigonometric beam by several typical homogeneous dielec- tric particles is investigated. The incident beam is represented by the vector expressions in Cartesian coordinates. The scattering problems involving homogeneous dielectric particles are formulated with the surface integral equation method. As an example, the effects of the beam＇s parameters on the differential scattering cross section for a sphere are analyzed in detail. Then the numerical results for the scattering of a high-order Bessel trigonometric beam by three typical nonspherieal particles, including a spheroid, a cylinder, and a cube, are presented.

Dwell Scheduling Algorithm for Digital Array Radar

Aiming at the problem of resource allocation for digital array radar（ DAR）,a dwell scheduling algorithm is proposed in this paper. Firstly,the integrated priority of different radar tasks is designed,which ensures that the imaging tasks are scheduled without affecting the search and tracking tasks; Then,the optimal scheduling model of radar resource is established according to the constraints of pulse interleaving; Finally,a heuristic algorithm is used to solve the problem and a sparse-aperture cognitive ISAR imaging method is used to achieve partial precision tracking target imaging. Simulation results demonstrate that the proposed algorithm can both improve the performance of the radar system,and generate satisfactory imaging results.