IMM-Based Ship-Borne Radar Target Tracking Algorithm

The Kalman filtering algorithm and commonly used maneuvering target tracking models in the target tracking are firstly studied in this paper, tracking performances of all models based on the Kalman filtering algorithm are simulated and analyzed. Then, multiple model target tracking algorithm is analyzed and studied, which uses multiple motion models to match different target motion models and exists interacting between all models. In this paper,the target tracking of shipboard radar is simulated with MATLAB. It shows the feasibility of the interacting multiple model algorithm composed of a CV model and a CA model. The simulation results indicate,this algorithm obtains a better performance in tracking high speed and high maneuvering targets and a better balance between the performance and computational complexity,as well as very practicability, which is suitable for the tracking target of shipboard radar tracking target.     

Multi-target tracking algorithm based on adaptive sampling interval in wireless sensor networks

Multi-target tracking is a hot topic of current research on wireless sensor networks (WSN). Based on adaptive sampling interval, we propose a multi-target tracking algorithm in order to save energy consumption and prevent tracking lost for WSN. We contrast the targets moving model by using the position metadata, and predicte the targets moving status based on extended Kalman filter (EKF).we adopt the probability density function (PDF) of the estimated targets to establish the tracking cluster. By defining the tracking center, we use Markov distance to quantify the election process of the main node (MN). We comput targets impact strength through the targets importance and the distance to MN node, and then use it to build tracking algorithm. We do the simulation experiment based on MATLAB, and the experiment results show that the proposed algorithm can accurate predict the trajectory of the targets, and adjust the sampling interval while the targets were moving. By analyzing the experiments data, we know that the proposed algorithm can improve the tracking precision and save the energy consumption of WSN obviously.     

The fall point arithmetic of rocket wreckage adopting atmosphere resistance modification

For the fall point calculation problem of Rocket Wreckage,the kinetic traits of rocket wreckage is analyzed, and the influence of the atmosphere resistance to wreckage fall point is studied mainly. The fall point algorithm of rocket wreckage adopting atmosphere resistance modification is proposed. Comparing with the traditional fall point algorithm, in the proposed method, the influence of layered atmosphere density of fall-point area is considered properly, and the air resistance coefficient is estimated according to the air dynamic equation of fall process, the integral method is adopted to get the moving track of the rocket wreckageand the final fall point. The effectiveness of the algorithm is validated by analyzing the fall points of the first stair of the rocket in four tasks corresponding to four types of rockets.     

Open-electrical impedance tomography with variation regularization algorithm

Open electrical impedance tomography (OEIT) with fixed electrode row is proposed to overcome the clinical application problems in closed electrical impedance tomography such as poor model adaptability, electrode position error, and inflexibility. Variation regularization algorithm (VRA) using variations function as regularization penalty term is proposed to save the more serious ill-posed inverse problem of OEIT. Simulation and experiment results show that the inverse problem of OEIT can be efficiently solved by VRA. The position, size and the relative value of conductivity of target at shallower position below electrodes can be clearly reflected by the restored image. OEIT is more potentially practical and effective in clinical applications.     

Adaptive visual tracking based on DSPCA

In order to solve the problem resulted from tracking drift of single reference color histograms,a sort of particle filtering algorithm based on DSPCA(decomposition-sparse-principal component-analysis) is presented. The image set with complementary is accessed by DSPCA,which is fused by means of the new similarity as the new object model. Compared with the basic particle filtering,visual tracking decomposition and adaptive multiple cues fusion tracking algorithm in challenging scenarios,the presented method can robustly track the object in fast motion and the object which is mostly blocked.     

Design of an Interacting Multiple Model Algorithm for Vehicle Target Tracking

The interacting multiple model algorithm is used to solve the vehicle's tracking problems in automated highway system.It has multiple models,each of which matches to a particular mode such as uniform motion with constant velocity and maneuvering motion with acceleration.Combined with the target maneuvering models,the current acceleration of the target and its covariance are simulated.Significant noise reduction is achieved during the uniform motion.And it does better in maintaining the accuracy of the state estimates than the unfiltered radar measurements during the maneuver.A rapid detection of the maneuver is also obtained.The Monte Carlo simulation results show that the IMM algorithm will improve the target's tracking performance and enhance the vehicle's safety and reliability.     

Realization of Intelligent Vehicle System for Target Recognition and Tracking

After analyzing target recognition and tracking technique, a method of developing specifically target tacking system is proposed, which uses digital image manipulation to target recognition. Software and hardware design of intelligent vehicle are presented in detail. The system uses digital image manipulation technology to cognize the certain target through a pickup camera installed on the front of the intelligent vehicle. When the target is moving, singlechip receives the commands from the computer and then control the vehicle to trace target. The system can run by itself, regardless of artificial control. This design provides a platform for the research of Growing Machine Intelligence system.     

The predictive control of an incremental model based on tracking error

An algorithm of incremental model predictive control is proposed to solve a class of industrial production process real-time tracking problems. The basic idea is to establish a predictive model by adopting speed response on the basis of tracking error, and realize the optimization of the second time performance by using the soft constraint of the increment of control quantity and the online rolling optimization method. The theoretical analysis and Matlab simulation results show that the control algorithm can obtain good tracking performance, smooth dynamic response of the controlled object and strong robustness of the closed-loop system.     

Research of Holospectrum Technique Based on Order Tracking

This paper analyzes the principle of THS(Traditional Holo-Spectrum) technique,and in allusion to the deficiency of THS that only can be used in stationary signal,a new holo-spectrum technique based on order tracking is proposed.By order tracking sampling technology,non-stationary signal in the time domain is transformed into stationary signal in the angle domain,then the THS technique can be applied.Through this way,the influence of non-stationary to THS is reduced and the application of THS is extended.The paper researches the principle of order tracking holo-spectrum and verified by a simulation experiment.The simulation result and error analysis demonstrate that this method can be valid used to analyze the non-stationary signal.The spectrum is distinct and the effect is apparent.     

Measurement of interharmonics in power network based on all phase FFT time shifting and phase difference

The harms brought by interharmonics have attracted people’s attention more and more. The research of interharmonics is based on the actual measurement of the interharmonics in power network. An interharmonics detection method of all phase fast Fourier transform (apFFT) time shifting and phase difference is proposed in order to overcome the defects of the bigger measurement error brought by traditional FFT algorithm. By adopting apFFT algorithm and adjusting sample rate, we suppress spectrum leakage of all 0.1 times integer time harmonics including fundamental. Frequency and amplitude corrections are obtained through main spectrum line phase difference. The apFFT main spectrum lines phase values without correction are directly taken as phase values. The concept is clear and the results are direct. The algorithm has the advantage of strong anti-interference between harmonics. The simulation results show that the proposed method can detect amplitude, phase and frequency of interharmonics with high precision. The algorithm provides a new effective way for power network interharmonic detection and analysis.     

Order Tracking Method Based on Time-Frequency Analysis

The fault character of moving parts of rotating machinery most time is speed related. The method of order spectrum analysis is more efficient than usual frequency analysis.Two general methods for realizing order tracking are discussed, and a new order tracking method based on time-frequency analysis is proposed. The time frequency order tracking method only depends on software for order tracking, which is a strong supplement to traditional methods, and specially satisfied the require of virtual instruments, so there is a good prospect for its using.     

Analysis of fast optimization algorithm for inverse detecting faulty insulators

In order to improve the computational efficiency of the insulator electric field inverse problem, the fast multi-pole method has been introduced to the traditional simulation charge method. Tikhonov regularization is used to process the ill-posed characteristic of inverse problem solution caused by the interference. Newton method is used to search the optimum solution, and then the actual field source parameters of insulators and the practical voltage distribution on the surface of the insulators can be obtained. The fast optimization algorithm has been verified in point charge model. And 110 kV insulator string is carried out to demonstrate that the fast optimization algorithm is much faster and more efficient than traditional method.     

Simulation of the constant modulus blind equilibrium algorithm with variable step size based on the mean square error

The mathematic models and basic theory of constant modulus algorithm (CMA) for blind channel equalization are introduced. An improved algorithm with variable step size is proposed based on CMA. The improved algorithm uses the mean square error (MSE) to obtain the new variable step size to solve the contradiction between the convergence rate and accuracy in traditional CMA with fixed step. To smooth the MSE learning curve for easy comparison, an ensemble average technique is used to analyze the performance of convergence with different step sizes. The theoretical analysis and the simulation results show that the improved algorithm is superior to the traditional constant modulus(CM) in terms of convergence speed and residual error.     

Performance analysis on improved PDA AI for moving target tracking

Aim at the problem that the EO imaging tracking system is inconsistent with the model of probabilistic data association with amplitude information (PDA AI), which supposes that the greater the amplitude value is, the greater the probability of being the tracked target will be, a modified PDA AI (MPDA AI) is presented . Based on the fact that the amplitude and the motion of the interested target are consistent in a short period, the MPDA AI models the amplitude information and the motion information of the target as well as their consistency with Markov stationary signal to analyze the association procedure of motion and amplitude. The lower bounds of Cramer Rao estimation error for PDA AI and MPDA AI are calculated and discussed in detail. The theoretical analysis and experimental results show that estimating the target motion with the MPDA AI will be more accurate and more reliable than estimating with the original PDA AI.     

Object-oriented Design of the Intelligent Decision-making System of Rocket Safety Controlling

Because of systemic error in measurement and trajectory track, precision of trajectory parameter is not high and it results in false alarms in the traditional systems. The intelligent decision-making system of rocket safe controlling is built by using object-oriented method. First, the authors analyze and design rocket safety controlling architecture. Then, we study about knowledge expressing and knowledge database by object-oriented technique for the rocket safety controlling. At last, inference procession of the system is discussed. Intelligent decision-making system of rocket safety controlling is accurate, extensible and flexible.     

A Fast Median Filtering Algorithm

A fast median filtering algorithm basing on the coherence of data in adjacent windows is presented.During median filtering,only the first median value is found by conventional squencing algorithm,the other median values are obtained by bisecting search method and quickinserting new element in sequenced window.For convenience of moving filter window along signal data,a data structure is desinged,which can make the new input element to cover output element and greatly reduce the quantity of computation.A 2-dimensional fast median filtering method by moving filter window along snack path is also introduced.     

A blind adaptive reduced-rank receiver for ultra-wideband communication systems

A low-complexity blind adaptive receiver for ultra-wideband (UWB) systems in the presence of both multiple access interference (MAI) and inter symbol interference (ISI) is proposed, which is composed of two stages. In the first stage, a reduced-rank algorithm based on the multi-stage Wiener filter (MSWF) is considered to suppress the MAI and extract multi-path components. Channel estimation using the projection approximation subspace tracking with deflation (PASTd) algorithm and multi-path combining are then performed to further enhance the signal to interference plus noise ratio (SINR) of the desired user in the second stage. The simulation results show that the proposed receiver exhibits reasonably good bit error ratio (BER) performance compared with those of matched filter, conventional Rake receiver, decorrelating Rake receiver and adaptive receiver based on constant modulus algorithm (CMA). Moreover, it has faster convergence speed and less complexity.     

An algorithm of symbol timing rapid acquisition and tracking for π/4 DQPSK signals

Methods of IF difference detection combined with rapid acquisition synchronization and tracking principle by parallel processing methods were proposed in order to quickly achieve synchronous digital capture and tracking in π/4 DQPSK demodulation.Field program grid array (FPGA) technology to achieve rapid detection of synchronous capture and symbol tracking was adopted by using the improved algorithm in parallel with signal acquisition and frequency offset acquisition. This adoption took into account the characteristics of π/4 DQPSK and was in accordance with the detection of rapid acquisition synchronization and the tracking principle. The experimental results show that clock synchronization signals can be restored stably in eight symbol bit, accurately realize bit timing, and possess strong anti interference capability without affecting frequency differences. This proposed algorithm is suited for frequency hopping communication systems with high transmission rates.     

Speedy Recognition of Noise in Real Time Signal Based on Wavelet Transform

It's necessary to process position and gesture of rocket on real time within the flight of rocket. This work should base exact data. But much noise has been found in the data and the noise recognize is regarded as a focus. A speedy online arithmetic recognizing noise is proposed based on wavelet transform. The computing complexity measured by time of this arithmetic is a constant which is greatly reduces the works of calculation of wavelet transform. It can recognize the noise fast when the signal is gathered. The applications in these problems show that the effective arithmetic satisfies the needs of real time and can handle the real time data measured in other yields.     

Design and apply the relative criticality arithmetic of ground protected objects

For the core problem of ground safety control—the relative criticality estimation of ground protected objects in the rocket launch process, the relative criticality algorithm of ground protected objects is proposed in the paper. This algorithm transforms the measurement of the relative criticality for ground protected objects into cost function which considers the rocket’s current fall point,the distribution of rocket’s wreckage and poison gas, the population and the important establishments of the objects, realize the comprehensive evaluation of the relative criticality for different objects. To verify the effectiveness of this algorithm, it is applied to a decision support system to achieve the quantitative evaluation of the ground protected objects in several rocket launching tasks. This algorithm provides quantificational judgment evidence for rocket safety control officers in effective decision- making for safety control of the rocket launching.