For the joint time difference of arrival (TDOA) and angle of arrival (AOA) location scene, two methods are proposed based on the rectangular coordinates and the polar coordinates, respectively. The problem is solved perfectly by calculating the target position with the joint TDOA and AOA location. On the condition of rectangular coordinates, first of all, it figures out the radial range between target and reference stations, then calculates the location of the target. In the case of polar coordinates, first of all, it figures out the azimuth between target and reference stations, then figures out the radial range between target and reference stations, finally obtains the location of the target. Simultaneously, simulation analyses show that the theoretical analysis is correct, and the proposed methods also provide the application of the joint TDOA and AOA location algorithm with the theoretical basis.

A new code concept is used for the L1 civil (L1C) signal of the global positioning system (GPS). The generation of L1C codes is quite different from the generation of traditional ranging codes. Thus, it is necessary to find a method for the correct generation to pave the way for future research. L1C codes are based on only one Legendre sequence which consists of Legendre symbols. To calculate these Legendre symbols, the Euler criterion is always used to evaluate quadratic residues. However, due to the great length of L1C codes, this procedure causes overflow problems. Therefore, the quadratic reciprocity law, some related theorems and properties are introduced to solve the problems. Moreover, if the quadratic reciprocity law, some related theorems and properties are used to calculate different Legendre symbols, the combination modes may vary, which causes a complex generation process. The proposed generation method deals with this complex generation process effectively. In addition, through simulations, it is found that the autocorrelation features of obtained Legendre sequences and L1C codes are in accordance with theoretical results, which proves the correctness of the proposed method.

A new combinational technology is proposed, which is feasible to apply physical-layer network coding (PNC) to wireless fading channels by employing the harmful interference strategically. The key step of PNC is that sources broadcast signals simultaneously without orthogonal scheduling. Naturally, the signals overlap in the free space at the receivers. Since the signals from different sources are mutual independent, rooted on this rational assumption, an enhanced joint diagonalization separation named altering row diagonalization (ARD) algorithm is exploited to separate these signals by maximizing the cost function measuring independence among them. This ARD PNC (APNC) methodology provides an innovative way to implement signal-level network coding at the presence of interference and without any priori information about channels in fading environments. In conclusions, the proposed APNC performs well with higher bandwidth utility and lower error rate.

An efficient compensation scheme combining a timedomain Gaussian elimination (GE) channel estimator and a frequency-domain GE equalizer is proposed for orthogonal frequency division multiplexing (OFDM) systems with frequencydependent in-phase and quadrature-phase (IQ) imbalances at both transmitter and receiver. Compared with the traditional least square and least mean square compensation schemes, the proposed compensation scheme achieves the same bit error rate as the ideal IQ branches by using only two training OFDM symbols instead of about 20 OFDM symbols.

This paper presents a novel robust S transform algorithm based on the clipping method to process signals corrupted by impulsive noise. The proposed algorithm is introduced to determine the clipping threshold value according to the characteristics of the signal samples. Signals in various impulsive noise models are considered to illustrate that the robust S transform can achieve better performance than the standard S transform. Moreover, mean square errors for instantaneous frequency estimation of the robust S transform are compared with that of the standard S transform, showing that the robust S transform can achieve significantly improved instantaneous frequency estimation for the signals in impulsive noise.

Cooperative communication can achieve spatial diversity gains, and consequently combats signal fading due to multipath propagation in wireless networks powerfully. A novel
complex field network-coded cooperation (CFNCC) scheme based on multi-user detection for the multiple unicast transmission is proposed. Theoretic analysis and simulation results demonstrate that, compared with the conventional cooperation (CC) scheme and network-coded cooperation (NCC) scheme, CFNCC would obtain higher network throughput and consumes less time slots. Moreover, a further investigation is made for the symbol error probability (SEP) performance of CFNCC scheme, and SEPs of CFNCC scheme are compared with those of NCC scheme in various scenarios for different signal to noise ratio (SNR) values.

For better interpretation of synthetic aperture radar (SAR) images, the speckle filtering is an important issue. In the area of speckle filtering, the proper averaging of samples with similar scattering characteristics is of great importance. However, existing filtering algorithms are either lack of a similarity judgment of scattering characteristics or using only intensity information for similarity judgment. A novel polarimetric SAR (PolSAR) speckle filtering algorithm based on the mean shift theory is proposed. As polarimetric covariance matrices or coherency matrices form Riemannian manifold, the pixels with similar scattering characteristics gather closely and those with different scattering characteristics separate in this hyperspace. By using the range-spatial joint mean shift theory in Riemannian manifold, the pixels chosen for averaging are ensured to be close not only in scattering characteristics but also in the spatial domain. German Aerospace Center (DLR) L-Band Experiment SAR (E-SAR) data and East China Research Institute of Electronic Engineering (ECRIEE) PolSAR data are used to demonstrate the efficiency of the proposed algorithm. The filtering results of two commonly used speckle filtering algorithms, refined Lee filtering algorithm and intensity driven adaptive neighborhood (IDAN) filtering algorithm, are also presented for the comparison purpose. Experiment results show that the proposed speckle filtering algorithm achieves a good performance in terms of speckle filtering, edge protection as well as polarimetric characteristics preservation.

According to the signal processing characteristic of MIMO radars, an adaptive dwell scheduling algorithm is proposed. It is based on a novel pulse interleaving technique, which makes full use of transmitting, waiting and receiving durations of radar dwells. The utilization of transmitting duration is unique for MIMO radars and is realized through transmitting duration overlapping. Simulation results show that, compared with the conventional scheduling algorithm, the scheduling performance of MIMO radars can be improved effectively by the proposed algorithm, and the scheduling rule can be chosen arbitrarily when using the proposed algorithm.

A Bayesian method for estimating human error probability (HEP) is presented. The main idea of the method is incorporating human performance data into the HEP estimation
process. By integrating human performance data and prior information about human performance together, a more accurate and specific HEP estimation can be achieved. For the time-unrelated task without rigorous time restriction, the HEP estimated by the common-used human reliability analysis (HRA) methods or expert judgments is collected as the source of prior information. And for the time-related task with rigorous time restriction, the human error is expressed as non-response making. Therefore, HEP is the time curve of non-response probability (NRP). The prior information is collected from system safety and reliability specifications or by expert judgments. The (joint) posterior distribution of HEP or NRP-related parameter(s) is constructed after prior information has been collected. Based on the posterior distribution, the point or interval estimation of HEP/NRP is obtained. Two illustrative examples are introduced to demonstrate the practicality of the aforementioned approach.

As an alternative or complementary approach to the classical probability theory, the ability of the evidence theory in uncertainty quantification (UQ) analyses is subject of intense
research in recent years. Two state-of-the-art numerical methods, the vertex method and the sampling method, are commonly used to calculate the resulting uncertainty based on the evidence theory. The vertex method is very effective for the monotonous system, but not for the non-monotonous one due to its high computational errors. The sampling method is applicable for both systems. But it always requires a high computational cost in UQ analyses, which makes it inefficient in most complex engineering systems. In this work, a computational intelligence approach is developed to reduce the computational cost and improve the practical utility of the evidence theory in UQ analyses. The method is demonstrated on two challenging problems proposed by Sandia National Laboratory. Simulation results show that the computational efficiency of the proposed method outperforms both the vertex method and the sampling method without decreasing the degree of accuracy. Especially, when the numbers of uncertain parameters and focal elements are large, and the system model is non-monotonic, the computational cost is five times less than that of the sampling method.

The problem of optimal aeroassisted symmetric transfer between elliptical orbits is concerned. The complete trajectory is assumed as consisting of two impulsive velocity changes at the beginning and the end of an interior atmospheric subarc, where the vehicle is controlled via the lift coefficient and thrust. The corresponding dynamic equations are built and bounded controls are considered. For the purpose of optimization computation, the equations are normalized. In order to minimize the total fuel consumption, the geocentric radius of initial elliptical transfer orbital perigee and controls during atmospheric flight should all be optimized. It is an optimal control problem which involves additional parameter optimization. To solve the problem, a two-level optimization method denoted by “genetic algorithm + Gauss pseudospectral method” is adopted: the genetic algorithm is used for parameter optimization and the Gauss pseudospectral method is used for optimal control problems. The flow chart of simulation is given. On this basis, the issue of more realistic modeling with two finite-thrust subarcs in the nonatmospheric part of the trajectory is simultaneously addressed. The orbital transfer problem
is transformed to three continuous optimal control problems, and the constraints at different times are given, which are respectively solved by using the Gauss pseudospectral method. The obtained numerical results indicate that the optimal thrust control is of bangbang type. The minimum-fuel trajectory in the atmosphere consists of aeroglide, aerocruise and aeroglide. They are compared with the results of pure impulsive model, and the conclusions that a significant fuel saving will be achieved by synergetic maneuver are drawn.

This paper proposes an adaptive augmentation control design approach of the gain-scheduled controller. This extension is motivated by the need for augmentation of the baseline gainscheduled controller. The proposed approach can be utilized to design flight control systems for advanced aerospace vehicles with a large parameter variation. The flight dynamics within the flight envelope is described by a switched nonlinear system, which is essentially a switched polytopic system with uncertainties. The flight control system consists of a baseline gain-scheduled controller and a model reference adaptive augmentation controller, while the latter can recover the nominal performance of the gainscheduled controlled system under large uncertainties. By the multiple Lyapunov functions method, it is proved that the switched nonlinear system is uniformly ultimately bounded. To validate the effectiveness of the proposed approach, this approach is applied to a generic hypersonic vehicle, and the simulation results show that the system output tracks the command signal well even when large uncertainties exist.

This paper develops a robust control methodology for a class of morphing aircraft, which is called innovative control effector (ICE) aircraft. For the ICE morphing aircraft, the distributed arrays of hundreds of shape-change devices are employed to stabilize and maneuver the air vehicle. Because the morphing aircraft have the inherent uncertainty and varying dynamics due to the alteration of their configuration, a desired control performance can not be satisfied with a fixed feedback controller. Therefore, a novel control framework including an adaptive flight control law and an adaptive allocation algorithm is proposed. Firstly, a state feedback adaptive control law is designed to guarantee closed-loop stability and state tracking in the presence of uncertain dynamics caused by the wing shape change due to different flight missions. In the control allocation, many distributed arrays are managed in an optimal way to improve the robustness of the system. The scheme is used to an uncertain morphing aircraft model, and the simulation results demonstrate their performance.

The focus of this paper is on control design and simulation for the longitudinal model of a flexible air-breathing hypersonic vehicle (FAHV). The model of interest includes flexibility effects and intricate couplings between the engine dynamics and flight dynamics. To overcome the analytical intractability of this model, a nominal control-oriented model is constructed for the purpose of feedback control design in the first place. Secondly, the multi-input multi-output (MIMO) quasi-continuous high-order sliding mode (HOSM) controller is proposed to track step changes in velocity and altitude, which is based on full state feedback. The simulation results are presented to verify the effectiveness of the proposed control strategy.

The consensus problem of the distributed attitude synchronization in the spacecraft formation flying is considered. Firstly, the attitude dynamics of a rigid body spacecraft is described by modified Rodriguez parameters (MRPs). Then global stable distributed cooperative attitude control laws are proposed for different cases. In the first case, the control law guarantees the state consensus during the attitude synchronization. In the second case, the control law ensures both the attitudes synchronizing to a desired constant attitude and the angular velocities converging at zero. In the third case, an attitude consensus control law with bounded control input is proposed. Finally, the effectiveness and validity of the control laws are demonstrated by simulations of six rigid bodies formation flying.

In order to improve the survival ability and rapid response ability of the carrier craft, a new rapid transfer alignment method of the strapdown inertial navigation system (SINS) on a rocking base is put forward. In the method, the aircraft carrier does not need any form of movement. Meantime, interfering motions such as rolling, pitching, and yawing motions caused by sea waves are effectively used. Firstly, the deck flexure deformation model is made. Secondly, the state space model of transfer alignment is presented. Finally, the feasibility of this method is validated by the simulation. Simulation results show that the misalignment angle error can be estimated and reach an anticipated precision— 0.2 mrad in 5 s, while the deck deformation angle error can be estimated and reach a better precision— 0.1 mrad in 20 s.

This paper develops the mean-square exponential input-to-state stability (exp-ISS) of the Euler-Maruyama (EM) method for stochastic delay control systems (SDCSs). The definition of mean-square exp-ISS of numerical methods is established. The conditions of the exact and EM method for an SDCS with the property of mean-square exp-ISS are obtained without involving control Lyapunov functions or functional. Under the global Lipschitz coefficients and mean-square continuous measurable inputs, it is proved that the mean-square exp-ISS of an SDCS holds if and only if that of the EM method is preserved for a sufficiently small step size. The proposed results are evaluated by using numerical experiments to show their effectiveness.

A generalized simulation method of the tracking, telemetry and control (TT&C) channel, which is applicable to wideband and arbitrary radio frequency (RF) signal, is proposed. It can accurately simulate the dynamic transmission delay of the arbitrary RF signal in channels, especially regardless of any prior knowledge including signal form, signal parameters, and so on. The proposed method orthogonally demodulates the wideband and arbitrary RF signal to complex baseband by a known local oscillator (LO) signal. Whereafter, it takes measures to obtain the delay reconstruction signal of baseband signals based on the dynamic transmission delay between a ground station and a responder. Meanwhile, it manages to obtain the delay reconstruction signal of LO signals. The simulation output signal (the delayed RF signal) can be achieved through the synthesis of the two delay reconstruction signals mentioned above. The principle and its related key technology are described in detail, and the realizable system architecture is given.

As for the drop of particle diversity and the slow convergent speed of particle in the late evolution period when particle swarm optimization (PSO) is applied to solve high-dimensional multi-modal functions, a hybrid optimization algorithm based on the cat mapping, the cloud model and PSO is proposed. While the PSO algorithm evolves a certain of generations, this algorithm applies the cat mapping to implement global disturbance of the poorer individuals, and employs the cloud model to execute local search of the better individuals; accordingly, the obtained best individuals form a new swarm. For this new swarm, the evolution operation is maintained with the PSO algorithm, using the parameter of pop distr to balance the global and local search capacity of the algorithm, as well as, adopting the parameter of mix gen to control mixing times of the algorithm. The comparative analysis is carried out on the basis of 4 functions and other algorithms. It indicates that this algorithm shows faster convergent speed and better solving precision for solving functions particularly those high-dimensional multi-modal functions. Finally, the suggested values are proposed for parameters pop distr and mix gen applied to different dimension functions via the comparative analysis of parameters.

With the development of global position system (GPS), wireless technology and location aware services, it is possible to collect a large quantity of trajectory data. In the field of data mining for moving objects, the problem of anomaly detection is a hot topic. Based on the development of anomalous trajectory detection of moving objects, this paper introduces the classical trajectory outlier detection (TRAOD) algorithm, and then proposes a density-based trajectory outlier detection (DBTOD) algorithm, which compensates the disadvantages of the TRAOD algorithm that it is unable to detect anomalous defects when the trajectory is local and dense. The results of employing the proposed algorithm to Elk1993 and Deer1995 datasets are also presented, which show the effectiveness of the algorithm.