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.

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.

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.

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.

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。

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.

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.

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.

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.

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.

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.

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.

Survey of visual just noticeable difference estimation

The concept of just noticeable difference (JND), which accounts for the visibility threshold (visual redundancy)of the human visual system,is useful in perceptionoriented signal processing systems.In this work,we present a comprehensive review of JND estimation technology.First, the visual mechanism and its corresponding computational modules are illustrated.These include luminance adaptation, contrast masking,pattern masking,and the contrast sensitivity function.Next,the existing pixel domain and subband domain YND models are presented and analyzed.Finally,the challenges associated with JND estimation are discussed.

Geometric optics interpretation for rainbow scattering of a chiral sphere

Research on light scattering from a large chiral sphere shows that the rainbow phenomenon is different from that of an isotropic sphere. A chiral sphere with certain chirality generates three first-order rainbows. In this Letter,we present a geometric optics interpretation for the phenomenon and make a calculation of the rainbow angles.The ray traces inside the sphere are determined by the reflection and refraction laws of light at the achiral–chiral interface and the chiral–achiral interface. The calculated rainbow angles achieve good agreements with those obtained by the analytical solutions. The effects of chirality and the refractive index of the sphere on rainbow angles are analyzed.

Low complexity asymptotically unitary algorithm for hybrid beamforming in mmWave communication systems

In millimeter wave （mmWave） massive multiple-input multiple-output （MIMO） systems, because of the high hardware cost and high power consumption, the traditional fully digital beamforming （DBF） cannot be implemented easily. Meanwhile, analog beamforming which is implemented with phase shifters has high availability but suffers poor performance. Considering the advantages of above two, a potential solution is to design an appropriate hybrid analog and digital beamforming structure, where the available iterative optimization algorithm can get performance close to fully digital processing, but solving this sparse optimization problem faces with a high computational complexity. The key challenge of seeking out hybrid beamforming （HBF） matrices lies in leveraging the trade-off between the spectral efficiency performance and the computational complexity. In this paper, we propose an asymptotically unitary hybrid precoding （AUHP） algorithm based on antenna array response （AAR） properties to solve the HBF optimization problem. Firstly, we get the optimal orthogonal analog and digital beamforming matrices relying on the channel＇s path gain in absolute value by taking into account that the AAR matrices are asymptotically unitary. Then, an improved simultaneously orthogonal matching pursuit （SOMP） algorithm based on recursion is adopted to refine the hybrid combining. Numerical results demonstrate that our proposed AUHP algorithm enables a lower computational complexity with negligible spectral efficiency performance degradation.

Hybrid beamforming with discrete phase shifters for millimeter wave backhaul networks

Hybrid beamforming（ HBF） technology becomes one of the key technologies in the millimeter wave（ mm Wave）mobile backhaul systems,for its lower complexity and low power consumption compared to full digital beamforming（ DBF）. Two structures of HBF exist in the mm Wave mobile backhaul system,namely,the fully connected structures（ FCS） and partially connected structures（ PCS）. However,the existing methods cannot be applied to both structures. Moreover,the ideal phase shifter is considered in some current HBF methods,which is not realistic. In this paper,a HBF algorithm for both structures based on the discrete phase shifters is proposed in the mm Wave mobile backhaul systems. By using the principle of alternating minimization,the optimization problem of HBF is decomposed into a DBF optimization problem and an analog beamforming（ ABF） optimization problem.Then the least square（ LS） method is enabled to solve the optimization model of DBF. In addition,the achievable data rate for both structures with closed-form expression which can be used to convert the optimization model into a single-stream beamforming optimization model with per antenna power constraint is derived. Therefore,the ABF is easily solved. Simulation results show that the performance of the proposed HBF method can approach the full DBF by using a lower resolution phase shifter.

Improved Q-learning algorithm for load balance in millimeter wave backhaul networks

With the intensive deployment of users and the drastic increase of traffic load, a millimeter wave （mmWave） backhaul network was widely investigated. A typical mmWave backhaul network consists of the macro base station （MBS） and the small base stations （SBSs）. How to efficiently associate users with the MBS and the SBSs for load balancing is a key issue in the network. By adding a virtual power bias to the SBSs, more users can access to the SBSs to share the load of the MBS. The bias values shall be set reasonably to guarantee the backhaul efficiency and the quality of service （QoS）. An improved Q-learning algorithm is proposed to effectively adjust the bias value for each SBS. In the proposed algorithm, each SBS becomes an agent with independent learning and can achieve the best behavior, namely the optimal bias value through a series of training. Besides, an improved behavior selection mechanism is adopted to improve the learning efficiency and accelerate the convergence of the algorithm. Finally, simulations conducted in the 60 GHz band demonstrate the superior performance of the proposed algorithm in backhaul efficiency and user outage probability.

Modified min-sum SCAN decoding algorithm for polar codes

The state-of-the-art soft-output decoder of polar codes is the soft cancellation(SCAN) decoding algorithm, which performs well at the cost of plentiful computations. Based on the SCAN decoding algorithm, a modified method with revised iterative formula is proposed, marked modified min-sum SCAN(MMS-SCAN). The proposed algorithm simplifies the update formula of nodes and reduces the complexity of iterative decoding process by the piecewise approximation function. Meanwhile, the bit error rate(BER) of the proposed method can approach the performance of original SCAN decoding method without performance loss. The simulation reveals that the MMS-SCAN decoding algorithm can achieve the effect that the BER curve almost coincides with the original SCAN decoding curve.

Gram-Schmidt based hybrid beamforming for mm Wave MIMO systems

Due to the high cost and power consumption of the radio frequency（RF） chains, it is difficult to implement the full digital beamforming in millimeter-wave（mm Wave） multiple-input multiple-output（MIMO） systems. Fortunately, the hybrid beamforming（HBF） is proposed to overcome these limitations by splitting the beamforming process between the analog and digital domains. In recent works, most HBF schemes improve the spectral efficiency based on greedy algorithms. However, the iterative process in greedy algorithms leads to high computational complexity. In this paper, a new method is proposed to achieve a reasonable compromise between complexity and performance. The novel algorithm utilizes the low-complexity Gram-Schmidt method to orthogonalize the candidate vectors. With the orthogonal candidate matrix, the slow greedy algorithm is avoided. Thus, the RF vectors are found simultaneously without any iteration. Additionally, the phase extraction is applied to satisfy the element-wise constant-magnitude constraint on the RF matrix. Simulation results demonstrate that the new HBF algorithm can make substantial improvements in complexity while maintaining good performance.