In laser-guided bomb attacking process, the target indication from the laser target designator is the premise for the bomb to hit the target accurately. Considering the lack of quantitative study of the irradiation area of the laser target designator, this paper, based on the existing aircraft motion model and the laser transmission model, uses two aircraft as respectively the carrier of the laser-guided bomb and the carrier of the laser designator and proposes a method to calculate the global irradiation area of the airborne laser designator. By using the proposed algorithm, the global irradiation area when attacking a large flat target or a large spherical target is simulated respectively. Finally, according to the simulation results, the influences of different factors on the shapes of the irradiation area are discussed in detail.

This paper proposes a parallel cyclic shift structure of address decoder to realize a high-throughput encoding and decoding method for irregular-quasi-cyclic low-density parity-check (IR-QC-LDPC) codes, with a dual-diagonal parity structure. A normalized min-sum algorithm (NMSA) is employed for decoding. The whole verification of the encoding and decoding algorithm is simulated with Matlab, and the code rates of 5/6 and 2/3 are selected respectively for the initial bit error ratio as 6% and 1.04%. Based on the results of simulation, multi-code rates are compatible with different basis matrices. Then the simulated algorithms of encoder and decoder are migrated and implemented on the field programmable gate array (FPGA). The 183.36 Mbps throughput of encoder and the average 27.85 Mbps decoding throughput with the initial bit error ratio 6% are realized based on FPGA.

Cyclotomic sequences have good cryptographic properties and are closely related to difference sets. This paper proposes a new class of binary generalized cyclotomic sequences of order two and length pqr. Its linear complexity, minimal polynomial, and autocorrelation are investigated. The results show that these sequences have a large linear complexity when 2 ∈D₁, which means they can resist the Berlekamp-Massey attack. Furthermore, the autocorrelation values are close to 0 with a probability of approximately 1-1/r. Therefore, when r is a big prime, the new sequence has a good autocorrelation.

An adaptive channel estimation algorithm for the channel length is proposed to construct a channel estimation model suitable for orthogonal frequency division multiplexing (OFDM) underwater acoustic communication signals for the dependence of traditional channel estimation algorithms on channel length information. This algorithm can be adopted to evaluate channel estimation quality in real time and to adaptively adjust the channel length of the channel estimation algorithm according to the evaluation result, which satisfies the need of accurate estimation of unknown underwater acoustic channels and communication application; based on the study on the relationship between the OFDM communication bit error rate and the subcarrier signal to noise ratio, a self-adjusting optimization scheme for OFDM subcarrier transmitting power is proposed, which realizes underwater communication with the low bit error rate through higher energy efficiency. The validity of the research content is verified through simulation and field experiments.

In the field of automatic target recognition and tracking, traditional image complexity metrics, such as statistical variance and signal-to-noise ratio, all focus on single-frame images. However, there are few researches about the complexity of image sequence. To solve this problem, a criterion of evaluating image sequence complexity is proposed. Firstly, to characterize this criterion quantitatively, two metrics for measuring the complexity of image sequence, namely feature space similarity degree of global background (FSSDGB) and feature space occultation degree of local background (FSODLB) are developed. Here, FSSDGB reflects the ability of global background to introduce false alarms based on feature space, and FSODLB represents the difference between target and local background based on feature space. Secondly, the feature space is optimized by the grey relational method and relevant features are removed so that FSSDGB and FSODLB are more reasonable to establish complexity of single-frame images. Finally, the image sequence complexity is not a linear sum of the single-frame image complexity. Target tracking errors often occur in high-complexity images and the tracking effect of low-complexity images is very well. The nonlinear transformation based on median (NTM) is proposed to construct complexity of image sequence. The experimental results show that the proposed metric is more valid than other metrics, such as sequence correlation (SC) and interframe change degree (IFCD), and it is highly relevant to the actual performance of automatic target tracking algorithms.

To track the nonlinear, non-Gaussian bearings-only maneuvering target accurately online, the constrained auxiliary particle filtering (CAPF) algorithm is presented. To restrict the samples into the feasible area, the soft measurement constraints are implemented into the update routine via the $\ell$₁ regularization. Meanwhile, to enhance the sampling diversity and efficiency, the target kinetic features and the latest observations are involved into the evolution. To take advantage of the past and the current measurement information simultaneously, the sub-optimal importance distribution is constructed as a Gaussian mixture consisting of the original and modified priors with the fuzzy weighted factors. As a result, the corresponding weights are more evenly distributed, and the posterior distribution of interest is approximated well with a heavier tailor. Simulation results demonstrate the validity and superiority of the CAPF algorithm in terms of efficiency and robustness.

The time difference of arrival (TDOA) estimation plays a crucial role in the accurate localization of the satellite interference source. In the dual-satellites interference source localization system, the target signal from the adjacent satellite is likely to be interfered by the normal communication signal with the same frequency. Therefore, the signal to noise ratio (SNR) of the target signal would become too low, and the TDOA estimation through cross-correlation processing would be unreliable or even unattainable. This paper proposes a technique based on blind separation to solve the co-channel interference problem, where separation of the mixed signal can be carried out by the particle filter (PF) algorithm. The experimental results show that the proposed method could achieve more accurate TDOA estimation. The measured data obtained by using the software radio platform at 915 MHz and 2 GHz respectively verify the effectiveness of the proposed method.

With the improvement of radar resolution, the dimension of the high resolution range profile (HRRP) has increased. In order to solve the small sample problem caused by the increase of HRRP dimension, an algorithm based on kernel joint discriminant analysis (KJDA) is proposed. Compared with the traditional feature extraction methods, KJDA possesses stronger discriminative ability in the kernel feature space. K-nearest neighbor (KNN) and kernel support vector machine (KSVM) are applied as feature classifiers to verify the classification effect. Experimental results on the measured aircraft datasets show that KJDA can reduce the dimensionality, and improve target recognition performance.

A joint resource allocation scheme concerned with the sensor subset, power and bandwidth for range-only target tracking in multiple-input multiple-output (MIMO) radar systems is proposed. By selecting an optimal subset of sensors with the predetermined size and implementing the power allocation and bandwidth strategies among them, this algorithm can help achieving a better performance within the same resource constraints. Firstly, the Bayesian Cramer-Rao bound (BCRB) is derived from it. Secondly, a criterion for minimizing the BCRB at the target location among all targets tracking in a certain range is derived. Thirdly, the optimization problem involved with three variable vectors is formulated, which can be simplified by deriving the relationship between the optimal power allocation vector and the bandwidth allocation vector. Then, the simplified optimization problem is solved by the cyclic minimization algorithm incorporated with the sequential parametric convex approximation (SPCA) algorithm. Finally, the validity of the proposed method is demonstrated with simulation results.

For the rapidly developing unmanned aerial vehicle (UAV) swarm, the system-of-systems (SoS) oriented design is a prospective conceptual design methodology due to the competence for complex mission requirements and subsystems interactions. In the SoS oriented design, the subsystems performance trade-off is the basis of design decisions. In the trade-off for surveillance missions, most previous works do not consider track reporting and mainly focus on the design of platforms. An improved method for the subsystems performance trade-off in the SoS oriented UAV swarm design is proposed. Within an improved design framework with subsystems disaggregation, this method is characterized by treating platforms, sensors, and communications as equally important subsystems, integrating operational strategies into the trade-off, and enabling the trade-off for track reporting. Those advantages are achieved by a behavior-based modular model structure for agent-based operational modeling and simulation. In addition, a method of analyzing the bounds of the communication range is also presented. Simulation experiments are conducted by using precision-based simulation replication rules and surrogate modeling methods. The results demonstrate the effectiveness of the proposed method, and show that the configuration of area partitioning changes the trade space of subsystems performances, indicating the necessity of integrating operational strategies into the conceptual design.

The distributed cooperative decision problems of missiles autonomous formation with network packet loss are investigated by using the potential game based on formation principles. In particular, a dynamic target allocation method for missiles formation is provided based on the potential game and formation principles, after the introduction of cooperative guidance and control system of the missiles formation. Then we seek the optimization of a global utility function through autonomous missiles that are capable of making individually rational decisions to optimize their own utility functions. The first important aspect of the problem is to design an individual utility function considering the characteristics of the missiles formation, with which the objective of the missiles are localized to each missile yet aligned with the global utility function. The second is to equip the missiles with an appropriate coordination mechanism with each missile pursuing the optimization of its own utility function. We present the design procedure for the utility, and present a coordination mechanism based on spatial adaptive play and then introduce the idea of "cyclical selected spatial adaptive play" and "negotiation based on time division multiple address (TDMA) protocol formation support network". Finally, we present simulations for the distributed dynamic target allocation on the comprehensive digital simulation system, and the results illustrate the effectiveness and engineering applicability of the method.

A retrieval control strategy for failed satellite, which is connected to a servicing spacecraft by a tether, is studied. The Lagrange analytical mechanics based dynamics modeling for the system composed of a servicing spacecraft, a tether and a failed satellite, is presented under the earth center inertia coordinate system, then model simplification is conducted under the assumption that the failed satellite's mass is far smaller than the servicing spacecraft's, meanwhile the tether's length is far smaller than the size of the servicing spacecraft's orbit. Analysis shows that the retrieval process is intrinsically unstable as the Coriolis force functions is a negative damping. A retrieval strategy based on only the tether's tension is designed, resulting in the fastest retrieval speed. In the proposed strategy, firstly, the tether's swing angle amplitude is adjusted to 45° by deploying/retrieving the tether; then the tether swings freely with fixed length until it reaches negative maximum angle -45°; finally, the tether is retrieved by the pre-assigned exponential law. For simplicity, only the coplanar situation, that the tether swings in the plane of the servicing spacecraft's orbit, is studied. Numerical simulation verifies the effectiveness of the strategy proposed.

For the problems of the consistency ranking of the group decision-making scheme, from the view of group negotiation and system coordination, the grey incidence analysis and Nash bargaining model are used to establish a consistency group decision-making method. First, the concepts of the consensus partial decision-making program and the consensus overall ideal decision-making program are defined, and then a multi-object optimization model is constructed based on the satisfaction maximization of group negotiation and deviation minimization of system coordination to determine the consensus partial decision-making program and the consensus overall ideal decision-making program. Moreover, the grey incidence analysis is exploited to measure the close degrees between them. Finally, a real case of the online product evaluation verifies the validity and rationality of the proposed model.

Strapdown inertial navigation system (SINS)/celestial navigation system (CNS) integrated navigation is widely used to achieve long-time and high-precision autonomous navigation for aircraft. In general, SINS/CNS integrated navigation can be divided into two integrated modes:loosely coupled integrated navigation and tightly coupled integrated navigation. Because the loosely coupled SINS/CNS integrated system is only available in the condition of at least three stars, the latter one is becoming a research hotspot. One major challenge of SINS/CNS integrated navigation is obtaining a high-precision horizon reference. To solve this problem, an innovative tightly coupled rotational SINS/CNS integrated navigation method is proposed. In this method, the rotational SINS error equation in the navigation frame is used as the state model, and the starlight vector and star altitude are used as measurements. Semi-physical simulations are conducted to test the performance of this integrated method. Results show that this tightly coupled rotational SINS/CNS method has the best navigation accuracy compared with SINS, rotational SINS, and traditional tightly coupled SINS/CNS integrated navigation method.

For a class of fractional-order linear continuous-time switched systems specified by an arbitrary switching sequence, the performance of PD^α-type fractional-order iterative learning control (FOILC) is discussed in the sense of L^p norm. When the systems are disturbed by bounded external noises, robustness of the PD^α-type algorithm is firstly analyzed in the iteration domain by taking advantage of the generalized Young inequality of convolution integral. Then, convergence of the algorithm is discussed for the systems without any external noise. The results demonstrate that, under some given conditions, both convergence and robustness can be guaranteed during the entire time interval. Simulations support the correctness of the theory.

The method of stabilizing switched systems based on the optimal control is applied, with all modes unstable, for a typical example of the multi-agent system. First, the optimal control method for stabilizing switched systems is introduced. For this purpose, a switching table rule procedure is constructed. This procedure is inspired by the optimal control that identifies the optimal trajectory for the switched systems. In the next step, the stability of a multi-agent system is studied, considering different unstable connection topologies. Finally, the optimal control method is successfully applied to an aircraft team, as an example of the multi-agent systems. Simulation results evaluate and confirm the successful application of this method in the aircraft team example.

Rotating machinery is widely used in the industry. They are vulnerable to many kinds of damages especially for those working under tough and time-varying operation conditions. Early detection of these damages is important, otherwise, they may lead to large economic loss even a catastrophe. Many signal processing methods have been developed for fault diagnosis of the rotating machinery. Local mean decomposition (LMD) is an adaptive mode decomposition method that can decompose a complicated signal into a series of mono-components, namely product functions (PFs). In recent years, many researchers have adopted LMD in fault detection and diagnosis of rotating machines. We give a comprehensive review of LMD in fault detection and diagnosis of rotating machines. First, the LMD is described. The advantages, disadvantages and some improved LMD methods are presented. Then, a comprehensive review on applications of LMD in fault diagnosis of the rotating machinery is given. The review is divided into four parts:fault diagnosis of gears, fault diagnosis of rotors, fault diagnosis of bearings, and other LMD applications. In each of these four parts, a review is given to applications applying the LMD, improved LMD, and LMD-based combination methods, respectively. We give a summary of this review and some future potential topics at the end.

The accurate quantification of human error probability (HEP) has long been a main pursuit for most human reliability analysis (HRA) methods. This paper proposes a strategy to analyze and predict human error on the basis of a further modification of the existing cognitive reliability and error analysis method (CREAM) in HRA. Through providing a broader definition for the key parameters used in the quantification method, this paper produces a relatively flexible strategy to determine the nominal HEP (HEP₀). Basing on this strategy, the actual quantification of HEP in CREAM is able to be applied to more verified conditions. To prove the validity of the method proposed, a case study of spacecraft launch is also introduced, in which the prediction derived from the method is proved consistent with real field data.