Multi-Bernoulli Filter for Tracking Multiple Targets Using Sensor Array

This paper presents a multi-Bernoulli filter for tracking the direction of arrival(DOAs)of time-varying number of targets using sensor array.Our method operates directly on the measurements of sensor array and does not require any detection.Firstly,more information is reserved and compared with the after-detection measurements using a finite set of detected points.It can significantly improve the tracking performance,especially in low signal-to-noise ratio.Secondly,it inherits the advantages of the multi-Bernoulli approximation which models each of the targets individually.This allows more accurate multi-target state estimation,especially when targets cross.The proposed filter does not need clustering step and simulation results showcase the improved performance of the proposed filter.

SIMULTANEOUS MULTIPLE TARGET RECOGNITION USING POLARIZATION AGILE WAVES

A novel matching method for simultaneous multi-target recognition is proposed by jointly considering target's prior scattering knowledge and the polarization parameters of radar echoes. The matching coefficients are calculated for the judgment. MATLAB simulations show that several targets can be accurately recognized simultaneously, and a high recognition probability can be achieved in Monte Carlo simulations. The total execution time can be remarkably reduced in the Field Programmable Gate Array (FPGA) implementation of the matching procedure.

DL0410,a candidate for anti-Alzheimer disease with multiple targets in multiple pathways

OBJECTIVE To find a promising candidate for anti-Alzheimer disease(AD)with multiple targets in multiple pathways.METHODS A series of classifiers were constructed for predicting the active compounds against 51 key targets toward Alzheimer disease(AD)using the multitargetquantitative structure-activity relationships(mt-QSAR)method.While drug screening assays were established to evaluate the predicted active molecules.In addition,various cellular models and animal models related with AD were set up to further study the effects of the active compounds.RESULTS A system for the discovery of Multitarget-Directed Ligands against AD was set up and applied,the predicted active compounds were validated by the drug screening assays,and several active compounds with multiple targets were discovered.Among them,DL0410 exerted high activity on H3R,α7n ACh R,ACh E and ERα,also displayed the most significant effect in improving the ability of memory and learning in several AD animal models.The study on its action mechanisms showed that it′s effect may partially through increasing neurotransmitter,inhibiting oxidative emergency,inhibiting the expression of APP,and promoting long-term potentiation.Besides,DL0410 is of more safety than the first-line clinical medicines.CONCLUSION DL0410 is a promising candidate for further development for AD treatment.

Modeling and simulation of torpedo acoustic homing trajectory with multiple targets

The characteristics of a torpedo＇s acoustic homing trajectory with multiple targets were studied. The differential equations of torpedo motion were presented based on hydrodynamics. The Fourth order Runge-Kutta method was used to solve these equations. Derived from sonar equations and Snell＇ s law, a simple virtual underwater acoustic environment was established for simulating the torpedo homing process. The Newton iteration method was used to calculate homing range and ray tracing was approximated by pieccwise line, which takes into consideration distortions cause by temperature, pressure, and salinity in a given sea area. The influence of some acoustic warfare equipment disturb the torpedo homing process in certain circumstances, including decoys and jammers, was alsotaken into account in simulations. Relative target identification logic and homing control laws were presented. Equal consideration during research was given to the requirements of rcal-timeactivity as well as accuracy. Finally, a practical torpedo homing trajectory simulation program was developed and applied to certain projects.

A combination algorithm of Chaos optimization and genetic algorithm and its application in maneuvering multiple targets data association

The most important problem in targets tracking is data association which may be represented as a sort of constraint combinational optimization problem. Chaos optimization and adaptive genetic algorithm were used to deal with the problem of multi-targets data association separately. Based on the analysis of the limitation of chaos optimization and genetic algorithm, a new chaos genetic optimization combination algorithm was presented. This new algorithm first applied the "rough" search of chaos optimization to initialize the population of GA, then optimized the population by real-coded adaptive GA. In this way, GA can not only jump out of the "trap" of local optimal results easily but also increase the rate of convergence. And the new method can also avoid the complexity and time-consumed limitation of conventional way. The simulation results show that the combination algorithm can obtain higher correct association percent and the effect of association is obviously superior to chaos optimization or genetic algorithm separately. This method has better convergence property as well as time property than the conventional ones.

Multiple Targets Recognition for Highly-Compressed Color Images in a Joint Transform Correlator

In this paper, we are proposing a compression-based multiple color target detection for practical near real-time optical pattern recognition applications. By reducing the size of the color images to its utmost compression, the speed and the storage of the system are greatly increased. We have used the powerful Fringe-adjusted joint transform correlation technique to successfully detect compression-based multiple targets in colored images. The colored image is decomposed into three fundamental color components images (Red, Green, Blue) and they are separately processed by three-channel correlators. The outputs of the three channels are then combined into a single correlation output. To eliminate the false alarms and zero-order terms due to multiple desired and undesired targets in a scene, we have used the reference shifted phase-encoded and the reference phase-encoded techniques. The performance of the proposed compression-based technique is assessed through many computer simulation tests for images polluted by strong additive Gaussian and Salt & Pepper noises as well as reference occluded images. The robustness of the scheme is demonstrated for severely compressed images (up to 94% ratio), strong noise densities (up to 0.5), and large reference occlusion images (up to 75%).

Range estimation based on symmetry polynomial aided Chinese remainder theorem for multiple targets in a pulse Doppler radar

To avoid Doppler ambiguity,pulse Doppler radar may operate on a high pulse repetition frequency(PRF).The use of a high PRF can,however,lead to range ambiguity in many cases.At present,the major efficient solution to solve range ambiguity is based on a waveform design scheme.It adds complexity to a radar system.However,the traditional multiple-PRF-based scheme is difficult to be applied in multiple targets because of unknown correspondence between the target range and measured range,especially using the Chinese remainder theorem(CRT)algorithm.We make a study of the CRT algorithm for multiple targets when the residue set contains noise error.In this paper,we present a symmetry polynomial aided CRT algorithm to effectively achieve range estimation of multiple targets when the measured ranges are overlapped with noise error.A closed-form and robust CRT algorithm for single target and the Aitken acceleration algorithm for finding roots of a polynomial equation are used to decrease the computational complexity of the proposed algorithm.

Design,synthesis,and biological evaluation of multiple targeting antimalarials

Malaria still threatens global health seriously today.While the current discoveries of antimalarials are almost totally focused on single mode-of-action inhibitors,multi-targeting inhibitors are highly desired to overcome the increasingly serious drug resistance.Here,we performed a structure-based drug design on mitochondrial respiratory chain of Plasmodium falciparum and identified an extremely potent molecule,RYL-581,which binds to multiple protein binding sites of P.falciparum simultaneously(allosteric site of type Ⅱ NADH dehydrogenase,Q_(o) and Q_(i) sites of cytochrome bc_(1)).Antimalarials with such multiple targeting mechanism of action have never been reported before.RYL-581 kills various drug-resistant strains in vitro and shows good solubility as well as in vivo activity.This structurebased strategy for designing RYL-581 from starting compound may be helpful for other medicinal chemistry projects in the future,especially for drug discovery on membrane-associated targets.

A multi-frame track-before-detect algorithm based on root label clustering for multiple targets

In this paper,a novel multi-frame track-before-detect algorithm is proposed,which is based on root label clustering to reduce the high computational complexity arising by observation area expansion and clutter/noise density increase.A criterion of track extrapolation is used to construct state transition set,root label is marked by state transition set to obtain the distribution information of multiple targets in measurement space,then measurement plots of multi-frame are divided into several clusters,and finally multi-frame track-before-detect algorithm is implemented in each cluster.The computational complexity can be reduced by employing the proposed algorithm.Simulation results show that the proposed algorithm can accurately detect multiple targets in close proximity and reduce the number of false tracks.

Estimation of detection threshold in multiple ship target situations with HF ground wave radar

A credible method of calculating the detection threshold is presented for the multiple target situations, which appear frequently in the lower Doppler velocity region during the surveillance of sea with HF ground wave radar. This method defines a whole-peak-outlier elimination （WPOE） criterion, which is based on in-peak-samples correlation of each target echo spectra, to trim off the target signals and abnormal disturbances with great amplitude from the complex spectra. Therefore, cleaned background noise samples are obtained to improve the accuracy and reliability of noise level estimation. When the background noise is nonhomogeneous, the detection samples are limited and often occupied heavily with outliers. In this case, the problem that the detection threshold is overvalued can be solved. In applications on experimental data, it is verified that this method can reduce the miss alarm rate of signal detection effectively in multiple target situations as well as make the adaptability of the detector better.

HEURISTIC QUANTUM GENETIC ALGORITHM FOR AIR COMBAT DECISION MAKING ON COOPERATIVE MULTIPLE TARGET ATTACK

In order to achieve the optimal attack outcome in the air combat under the beyond visual range(BVR)condition,the decision-making(DM)problem which is to set a proper assignment for the friendly fighters on the hostile fighters is the most crucial task for cooperative multiple target attack(CMTA).In this paper,a heuristic quantum genetic algorithm(HQGA)is proposed to solve the DM problem.The originality of our work can be supported in the following aspects:(1)the HQGA assigns all hostile fighters to every missile rather than fighters so that the HQGA can encode chromosomes with quantum bits(Q-bits);(2)the relative successful sequence probability(RSSP)is defined,based on which the priority attack vector is constructed;(3)the HQGA can heuristically modify quantum chromosomes according to modification technique proposed in this paper;(4)last but not the least,in some special conditions,the HQGA gets rid of the constraint described by other algorithms that to obtain a better result.In the end of this paper,two examples are illustrated to show that the HQGA has its own advantage over other algorithms when dealing with the DM problem in the context of CMTA.

Implementation of non-local quantum controlled-NOT gate with multiple targets

We show how a non-local quantum controlled-NOT (CNOT) gate with multiple targets can be implemented with unit fidelity and unit probability.The explicit quantum circuit for implementing the operation is presented.Two schemes for probabilistic implementing the operation via partially entangled quantum channels with unit fidelity are put forward.The overall physical resources required for accomplishing these schemes are different,and the successful implementation probabilities are also different.

CHIP regulates bone mass by targeting multiple TRAF family members in bone marrow stromal cells

Carboxyl terminus of Hsp70-interacting protein（CHIP or STUB1） is an E3 ligase and regulates the stability of several proteins which are involved in different cellular functions. Our previous studies demonstrated that Chip deficient mice display bone loss phenotype due to increased osteoclast formation through enhancing TRAF6 activity in osteoclasts. In this study we provide novel evidence about the function of CHIP. We found that osteoblast differentiation and bone formation were also decreased in Chip KO mice. In bone marrow stromal（BMS） cells derived from Chip^-/- mice, expression of a panel of osteoblast marker genes was significantly decreased. ALP activity and mineralized bone matrix formation were also reduced in Chip-deficient BMS cells. We also found that in addition to the regulation of TRAF6, CHIP also inhibits TNFα-induced NF-κB signaling through promoting TRAF2 and TRAF5 degradation. Specific deletion of Chip in BMS cells downregulated expression of osteoblast marker genes which could be reversed by the addition of NF-κB inhibitor. These results demonstrate that the osteopenic phenotype observed in Chip^-/- mice was due to the combination of increased osteoclast formation and decreased osteoblast differentiation. Taken together, our findings indicate a significant role of CHIP in bone remodeling.

Multiple extended target tracking algorithm based on Gaussian surface matrix

In this paper, we consider the problem of irregular shapes tracking for multiple extended targets by introducing the Gaussian surface matrix（GSM） into the framework of the random finite set（RFS） theory. The Gaussian surface function is constructed first by the measurements, and it is used to define the GSM via a mapping function. We then integrate the GSM with the probability hypothesis density（PHD） filter, the Bayesian recursion formulas of GSM-PHD are derived and the Gaussian mixture implementation is employed to obtain the closed-form solutions. Moreover, the estimated shapes are designed to guide the measurement set sub-partition, which can cope with the problem of the spatially close target tracking. Simulation results show that the proposed algorithm can effectively estimate irregular target shapes and exhibit good robustness in cross extended target tracking.

Revolutionary entrapment model of uniformly distributed swarm robots in morphogenetic formation

This study proposes a method for uniformly revolving swarm robots to entrap multiple targets,which is based on a gene regulatory network,an adaptive decision mechanism,and an improved Vicsek-model.Using the gene regulatory network method,the robots can generate entrapping patterns according to the environmental input,including the positions of the targets and obstacles.Next,an adaptive decision mechanism is proposed,allowing each robot to choose the most well-adapted capture point on the pattern,based on its environment.The robots employ an improved Vicsek-model to maneuver to the planned capture point smoothly,without colliding with other robots or obstacles.The proposed decision mechanism,combined with the improved Vicsek-model,can form a uniform entrapment shape and create a revolving effect around targets while entrapping them.This study also enables swarm robots,with an adaptive pattern formation,to entrap multiple targets in complex environments.Swarm robots can be deployed in the military field of unmanned aerial vehicles’(UAVs)entrapping multiple targets.Simulation experiments demonstrate the feasibility and superiority of the proposed gene regulatory network method.

New targets number estimation method under colored noise background

A multiple targets detection method based on spatial smoothing （MTDSS） is proposed to solve the problem of the source number estimation under the colored noise background. The forward and backward smoothing based on auxiliary vectors which are received data on some specific elements is computed. By the spatial smoothing with auxiliary vectors, the correlated signals are decorrelated, and the colored noise is partially alleviated. The correlation matrix formed from the cross correlations between subarray data and auxiliary vectors is computed. By exploring the second-order statistics property of the covariance matrix, a threshold based on Gerschgorin radii of the smoothing correlation matrix is set to estimate the number of sources. Simulations and experimental results validate that MTDSS has an effective performance under the condition of the colored noise background and coherent sources, and MTDSS is robust with the correlated factor of signals and noise.

STOCHASTIC NEURAL NETWORK AND ITS APPLICATION TO MULTI－MANEUVERING TARGET TRACKING

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Posterior Cramer-Rao lower bounds for multitarget bearings-only tracking

Usually, only the Cramer-Rao lower bound （CRLB） of single target is taken into consideration in the state estimate of passive tracking systems. As for the case of multitarget, there are few works done due to its complexity. The recursion formula of the posterior Cramer-Rao lower bound （PCRLB） in multitarget bearings-only tracking with the three kinds of data association is presented. Meanwhile, computer simulation is carried out for data association. The final result shows that the accuracy probability of data association has an important impact on the PCRLB.

Distance to Isocenter Directly Affects Margin and Inappropriate Margin Increases the Risk of Local Control Failure in LINAC-Based Single-Isocenter SRS or SRT for Multiple Brain Metastases

=In the advancement of single-isocenter multiple target treatment in the LINAC-based SRS or SRT, the target distance to the isocenter and grouping of multiple targets are the highly concerned and debatable topics in the SRS/SRT field at present. Three failure and success cases of local control in our early practices are presented in this study and it indicated that the target distance to the isocenter directly affects the margin and an inappropriate margin increase the risk of local control failure. The GTV expansion margin should be LINAC-specific and institute-specific. Within the physics and dosimetry scope, the AHARA (as high as reasonably achievable) principle is the first time proposed to the radiation oncology field. Radiobiology and tumor response complexity is beyond this study.

Signal decomposition of HF radar maneuvering targets by using S^2-method with clutter rejection

Multiple maneuvedng targets signal processing in high frequency radar is challenging due to the following difficulties： the interference between signals is severe because of significant spread of the target Doppler spectrum, the low signal to clutter ratio （SCR） environment degrades the performance of signal process- ing algorithms. This paper addresses this challenging problem by using an S2-method and an adaptive clutter rejection scheme. The proposed S2-method improves the S-method by eliminating inter- ference between signals, and thus it enables multi-target signals to be reconstructed individually. The proposed adaptive clutter rejec- tion scheme is based on an adaptive notch filter, which is designed according to the envelop of the clutter spectrum. Experiments with simulated targets added into radar sea clutter echo and real air target data illustrate the effectiveness of the proposed method.