For squint terrain observation by progressive scans (TOPS) synthetic aperture radar (SAR) mode, this paper proposes a new full-aperture imaging algorithm. Firstly, the two dimensional (2-D) spectrum without aliasing is obtained by the azimuth pre-processing after range walk correction. Then the modified chirp scaling algorithm is used to complete range compression and range cell migration correction (RCMC). After that, by using a frequency nonlinear chirp scaling (FNCS) method in the range Doppler domain, the variation of the FM rates is corrected, and the signal is focused in the Doppler domain by SPECAN technique. Finally, geometric distortion correction is carried out. Both simulation and real data processing results demonstrate the effectiveness of the proposed method.

The inherent delay-Doppler coupling in stepped-chirp radar has a severe impact on range and velocity measurement. Based on the analysis of its Doppler performance, the rough range is firstly achieved according to the sampling time and thus the rough velocity is gotten through the range-velocity coupling, which will be used in compensation for the quadratic item of echo phase. Then the waveform of frequency domain is analyzed to get the precise range of each scatter center, and finally the precise velocity is obtained. The new method of resolving the range-velocity coupling is analyzed in detail and the steps of range and velocity measurement based on frequency-domain waveform analysis are given. Simulation results prove that this method has a better performance at a high sampling rate and non-ambiguous velocity.

By the research of sampling survey and radio propagation,a novel method on sampling and analysis of field test data is introduced.According to the theory of sampling survey,cluster analysis is introduced to finish the sort.Then a method on analysis of field test is presented by using cluster sawpling and two-stage sawpling.In order to improve the reliability of field test data,by the estimation theory of sample size,a method of field test route choice is introduced based on wireless network planning.

The threshold of the traditional Canny algorithm needs to be set by manual,and its computation is complex.To overcome these shortcomings of the traditional Canny algorithm,A method of threshold-adaptable edge detection and its implementation in hardware are proposed.Based on the gradient histogram,the two thresholds can be found and the edge can be detected automatically.It is meanwhile recommended that an implementation of this edge detection is carried on in field programmable gate array(FPGA).Experiments show that compared with the traditional Canny algorithm,this method can detect edge automatically and needs much less time consumption.

A testing methodology for the system maximumerror specification based on the extreme value theory is proposed. It an  provide a theoretic basis for the testing of maximumerror specification on longworking systems in some special  fields, such as aviation, aeronautics and national defenses. Firstly, the error series of system outputs is divided into  blocks by obeying some essential principals, and the corresponding maximum error series  which are nearly independent  with each other are gotten. Secondly, the extreme value models for the maximum error series are built and the return  level and its uncertainty are obtained under some return period. Then,  the relationships between the return level and  the maximumerror specification are researched and the system maximumerror specification is tested and evaluated by  using classic statistical theories. After that, a practical sample is given to introduce the methodology more clearly,  which shows that this methodology is feasible. Finally, by comparing the proposed methodology with that based on the time  series models from different points of view, some conclusions are given.

First, based on the influence of the discretization scheme on the inference function, the conditional information entropy is proposed to evaluate the discretization scheme; second, in order to reduce the complexity of problem solving, the whole network is proposed to divide into many minimum simple sub-networks and every one is discretized respectively; third, based on the similarity between discretization and path planning, an ant colony algorithm is used to problem solving. Experimental results show that the proposed method could do well in discretization of continuous variables so as to improve the inference performance.

The fluctuation of received signal strength (RSS) and access points (AP) outage are the major limit to wireless local area network (WLAN) based positioning accuracy. This paper proposes a data fusion algorithm based on particle filter and Kalman filter in order to realize a low-cost, high-precision WLAN/ magnetic, angular rate, and gravity (MARG) integrated positioning system using MARG sensors in the Smartphone. The system fuses the complementary information from WLAN and MARG positioning techniques to correct the positioning error due to the fluctuation of RSS and the accumulative error of the sensors due to senor noises. The experimental results in indoor WLAN environments indicate that the positioning accuracy of the proposed system is reduced by 62% and 91%, respectively, as compared with WLAN-based system and MARG-based system. Meanwhile, the scope of positioning is also effectively expanded.

Considering the divergence phenomenon of extenthed Kalman filter (EKF) in SINS/GPS tightly integrated navigation system, a square root unscented Kalman filter (QSRUKF) algorithm based on quaternion  is proposed. In order to ensure normalization of unit quaternion in SRUKF algorithm, an attitude matrix cost function is established to solve the problem of predicted average quaternion by minimizing the cost function; the multiplicative quaternion error is used to predict covariance, since it represents the distance between predicted quaternion and mean quaternion. On the basis, the specific steps of QSRUKF in SINS/GPS integrated navigation system are given. Simulation results show that the proposed algorithm has higher precision and stronger robustness under the larger initial attitude error angle compared with the EKF algorithm.

Aiming at the defects of slow rate of convergence, low accuracy and easily falling into local optimum in  artificial fish swarm algorithm (AFSA), an improved AFSA is proposed. In order to improve the accuracy, polar coordinate coding is introduced to increase the diversity in the expression solution of single matrix solution space. The polar angle is adjusted under probability by fitness in iterative process, and the uncertainty of observational results is reduced gradually. In order to increase the rate of convergence, three kinds of actions are adjusted, the random move which impacts the search direction is removedm, the search focuses on the neighborhood of the optimal solution and the possibility of repetition search is reduced. Experimental results show that the convergence and the stability of this algorithm are better than those of AFSA, adaptive artificial fish swarm algorithm (AAFSA) and niche artificial fish swarm algorithm (NAFSA), and the effectiveness of the algorithm is validated.

The expressions of non-conjugated and conjugated secondorder cyclic cumulants are deduced based on complexvalued binary phase shift keying (BPSK) signals. The influence of different timedelays on the characteristics of cyclic frequency is studied, and the independent algorithms are proposed to estimate carrier frequency and chip width. In other words, carrier frequency can be estimated based on nonconjugated secondorder cyclic cumulants with a timedelay to be zero|while chip width can be estimated based on conjugated  second order cyclic cumulants with a timedelay to be nonzero. To improve the performance, the optimum timedelay is deduced, and then a much better chip width estimation algorithm is proposed. Simulations verify that though the performance of the proposed carrierfrequency algorithm has 2 dB loss, computational complexity is much simpler than the cyclicspectrum algorithm, and the performance of the proposed chip width algorithm has a more than 5 dB increase compared with the cyclicspectrum algorithm.

The algorithm for maintaining materialized outerjoin views is proposed to compute the secondary delta by the independent computation of terms. In this algorithm, select project outer join (SPOJ) views are rewritten as the join disjunctive normal form first. Then the independent computation of terms is derived from every normal term. Finally common sub expressions extracted from all of the computation terms are utilized to compute the secondary delta of materialized outer join views. Experimental results show that the algorithm can reduce the computational cost effectively compared with other counterparts under the same conditions, and furthermore it poses no restrictions on SPOJ views.

A new adaptive estimation method of Kalman filter fading factor is presented from the stability of Kalman filter. The fading filter matrix is introduced, and the fading factor is adjusted adaptively on line based on the uncorrelated character of residual, so the fading filter works in the optimal state. The adaptive fading filter is applied in transfer alignment of inertial navigation systems (INS), the result shows the proposed algorithm is better than other algorithm when the prior data of model and noise character is unaccurate.

In order to eliminate the possible risk  existing in the development of automatic test systems (ATS) due to the lack of effective verification, an effectiveness evaluation system (EES) of ATS is proposed. According to the characteristics that the military ATS puts more stress on promotion of test time and ability, the ADC evaluation architecture is set up, and integrating the analytic hierarchy process, the EES based on operation domain is built, which solves the problem of distributing weight of system ability. A math evaluation model of ATS ability and its sub target are put forward. The proposed system provides an effective way to control cost, analyze feasibility and demonstrate risk for ATS.

Performance analysis for the track association algorithm is an unsolved issue in the space-based optical passive tracking system. A novel method is proposed to analyze the performance of the two dimensional assignment track association algorithm based on the hinge angle difference statistic. Firstly, the probability distribution of the hinge angle difference statistic is modeled exactly in the correct and the wrong association situation, respectively. Then, the equivalent condition of the association algorithm is analyzed. Finally, the theoretic performance of this algorithm is derived. Theoretic performance and Monte-Carlo simulation results show that the track association performance is mainly affected by the measurement angle errors, the separation and the direction difference between targets. It seems that this research can provide references to engineering applications.

To apply prognostics and health management (PHM) technology in realistic engineering, a method of PHM based on availability model is proposed. Firstly, the hardware and software model of the basic unit and its healthy state transition diagram are established by generalized stochastic Petri nets (GSPN) and continuous time Markov chain (CTMC). The availability of the basic unit could be calculated by sloving differential equations. Combining the relationship of the hardware and software faults, the unit availability model is obtained. Based on event scheduling simulation, the result of the basic unit availability is achieved. Finally, a comparison is made between the failure model of the basic uint and the model of repairable system theory, the “availability-failure rate-maintenance rate” calculation model is obtained and is applied for PHM analysis in engineering.

According to the marine’s mooring condition and the influence of the inertial elements bias on the navigation precision, a single-axis indexing scheme with four positions and the systematic error function are proposed . The analytic method which is used to analyse the observability of parameters directly is researched. The degree of observability for strapdown inertial navigation systems is computed in the context of resting and rotating inertial measurement units respectively with the spectral condition number theory, and the field estimation of inertial bias is achieved by the introduction of Kalman filter with the position loop isolation. Finally, numerical simulations show that the degree of observability for inertial bias can be improved effectively, and the estimation precision can also be improved greatly.

The Gaussian sum recursive algorithms for nonlinear non-Gaussian state space models, on the assumption that the process and measurement noises are denoted by Gaussian-sums, is firstly deduced. And then the corresponding extended Kalman sum filter (EKSF) and the Gauss-Hermite sum filter (GHSF) are proposed, which use the extended Kalman filter (EKF) and Gauss-Hermite filter (GHF) as the Gaussian sub-filter respectively. The analysis shows that the existing Gaussian sum filtering algorithms are nothing but special casesof the deduced algorithm. The simulation results show that the proposed EKSF and GHSF can deal with the state estimation of the nonlinear non-Gaussian models effectively, and only consume about 5% and 6% of the computing time required by the Gaussian sum particle filter (GSPF), while the consistent filtering performance is kept.

With the advantages of high flexibility, wide adaptability, and controllable economical efficiency, the unmanned aerial vehicle swarm has plenty of applications, and has attracted great attentions at home and abroad. Mission planning is the top-level planning of unmanned aerial vehicle cluster application. It is a compre-hensive scheduling according to the requirements of mission environment situation, task requirements and its own characteristics, so as to establish a reasonable mapping relationship between unmanned aerial vehi-cle and task, and maintain a reasonable cooperative relationship among unmanned aerial vehicles. The present situation of mission planning technology for the unmanned aerial vehicle is summarized comprehensively from two different aspects. One is based on the rule, style of top-down, and the other is based on the swarm intelligence, style of down-top. Some development directions of current mission planning technology research for the unmanned aerial vehicle swarm are analyzed. The summary has important reference significance for the comprehensive understanding of mission planning technology of the unmanned aerial vehicle swarm.

For the sake of reducing computation complexity caused by the subspace decomposition step in most of the state of the art subspace based algorithms for direction-of-arrival (DOA) estimation, a joint crosscovariance matrix (JCCM) based algorithm is proposed using a uniform linear array (ULA). Based on the ideas of array division and matrix remodeling, the ULA is divided into two subarrays, and two crosscovariance matrices are computed by the received datum of the two subarrays, with which a JCCM matrix is further reconstructed. Combing those three matrices, an equivalent signal subspace is found by conducting some lowcomplexity linear operations, and a polynomial is finally constructed to estimate source DOA without subspace decomposition. Theoretical analysis and simulation results show that the proposed technique can provide acceptable performances with the computational complexity effectively reduced and the faster estimation speed achieved.

A wartime repairable spares support planning model is presented based on the three-echelon support structure, in which multi-stage characteristic is considered. The stage expected number of backorders is taken as the performance parameter; both its definition and expressions are given. The iterative method is adopted to get the optimized strategy, the computing process is given considering the destroyed spare can all be repaired or not. Based on the dynamic Palm theory, how to compute the expected number of backorders is illustrated when spare numbers in pipeline is Poisson distribution. An example is given in the end.

In condition of transonic flight, the performance of the angle of attack (AOA) sensor declines remarkably which influences the normal flight seriously. Aiming at the different configurations of AOA sensors when the plane is in flight-test and in equipment and the shortage of tranditional back-propagation (BP) algorithm, an algorithm based on improved BP algorithm (Levenberg Marquardt algorithm, LM algorithm) is designed to compensate and correct the transonic AOA. The BP neural network based on LM algorithm has been trained and tested with actual flight data. The results show that the AOA, which is corrected by the BP neural network as compensation, could basically eliminate the violent fluctuations of the measured AOA in transonic phase. And its tendency coincides with the true AOA with a small error.

A blind timing synchronization method using the cyclostationary feature of received signals of multiple bases cooperation multiple input multiple output (MIMO) orthogonal frequency division multiplexing（OFDM） transmission systems is proposed. Owing to the shift of the received signal cyclic autocorrelation peak, the delay difference among antennas is derived. A detection method based on sliding-window is designed to get the timing delay of each antenna. The simulation results prove this method can sovle the problem of ditributed multiple antennas timing synchronization with acceptable complexity.

An fusion algorithm for synthetic aperture radar (SAR) and panchromatic images based on multi-level threshold segmentation and the nonsubsampled Contourlet transform(NSCT) is proposed. Firstly, multi-level threshold segmentation is done for the despeckle SAR image, and the measurement named ratio of region mean(RRM) is presented to divide the SAR image into several regions. Then the NSCT is performed on the despeckle SAR image and the panchromatic image at different scales and directions. The low-frequency coefficients are fused with the region-based fusion scheme according to the RRM, and the high-frequency coefficients are fused with the windows-based rules and region-based rules. Finally the fused coefficients are reconstructed to obtain the fused image. Experimental results show that the fused image can not only preserves the spatial resolution of the panchromatic image but also effectively join the target information of the SAR image. The algorithm performs significantly better than the wavelet transform and the pixel-based NSCT.

Because of the extremely low signal-to-noise ratio (SNR) of pulsar signals, it is difficult for the traditional denoise algorithms to suppress noise while preserving details such as micro-pulses. Therefore a new denoising algorithm which is based on the improved wavelet spatial correlation filtering is proposed. Firstly, the defects of the wavelet threshold and spatial correlation denoising algorithms in the extremely weak pulsar signals’ processing are analysed. Then, the wavelet spatial correlation filtering algorithm is improved according to the characteristics of pulsar signals, such as strict periodicity, correlation of adjacent periods, low SNR, radiation in the window and so on. Finally, the experiments are made with the pulsar signal observed by the Parks observatory and Rossi X-ray timing explorer. The results show that the proposed algorithm can preserve more details and provide a notable improvement in SNR.

In view of the weaknesses of neglecting battlefield environment uncertainty of command and control (C2) organization in classical “task-platform” relation design (TPRD), a C2 organization structure “task-platform” relation design under uncertainty (TPRDU) is investigated to improve the practicality. TPRDU considers mission success uncertainty, mission time uncertainty and platform capability consumption uncertainty. 〖JP2〗A chance-constrained programming model with mission success probability (MSP) maximization objective for TPRDU is built and a scatter search (SS) algorithm to solve this model is designed. The SS algorithm uses the strategy of platform redundancy design (PRD) during generating the new solution. Finally, experimental results illustrate the practicality of TPRDU and the efficiency of SS, and validate that MSP can be improved through PRD strategy.