Waveform diversity based sonar system for target localization

A new monostatic array system taking advantage of diverse waveforms to improve the performance of underwater tar- get localization is proposed. Unlike the coherent signals between different elements in common active array, the transmitted signals from different elements here are spatially orthogonal waveforms which allow for array processing in the transit mode and result in an extension of array aperture. The mathematical derivation of Capon estimator for this sonar system is described in detail. And the performance of this orthogonal-waveform based sonar is an- alyzed and compared with that of its phased-array counterpart by water tank experiments. Experimental results show that this sonar system could achieve 12 dB-15 dB additional array gain over its phased-array counterpart, which means a doubling of maximum detection range. Moreover, the angular resolution is significantly improved at lower SNR.

Ground target localization algorithm for semi-active laser terminalcorrection projectile

A target localization algorithm,which uses the measurement information from onboard GPS and onboard laser detector to acquire the target position,is proposed to obtain the accurate position of ground target in real time in the trajectory correction process of semi-active laser terminal correction projectile.A target localization model is established according to projectile position,attitude and line-of-sight angle.The effects of measurement errors of projectile position,attitude and line-of-sight angle on localization accuracy at different quadrant elevation angles are analyzed through Monte-Carlo simulation.The simulation results show that the measurement error of line-of-sight angle has the largest influence on the localization accuracy.The localization accuracy decreases with the increase in quadrant elevation angle.However,the maximum localization accuracy is less than 7 m.The proposed algorithm meets the accuracy and real-time requirements of target localization.

Moving target localization for multistatic passive radar using delay, Doppler and Doppler rate measurements

Time delay and Doppler shift between the echo signal and the reference signal are two most commonly used measurements in target localization for the passive radar. Doppler rate, which can be obtained from the extended cross ambiguity function, offers an opportunity to further enhance the localization accuracy. This paper considers using the measurement Doppler rate in addition to measurements of time delay and Doppler shift to locate a moving target. A closed-form solution is developed to accurately and efficiently estimate the target position and velocity.The proposed solution establishes a pseudolinear set of equations by introducing some additional variables, imposes weighted least squares formulation to yield a rough estimate, and utilizes the function relation among the target location parameters and additional variables to improve the estimation accuracy. Theoretical covariance and Cramer-Rao lower bound(CRLB) are derived and compared, analytically indicating that the proposed solution attains the CRLB. Numerical simulations corroborate this analysis and demonstrate that the proposed solution outperforms existing methods.

Improved Weighted Local Contrast Method for Infrared Small Target Detection

In order to address the problem of high false alarm rate and low probabilities of infrared small target detection in complex low-altitude background,an infrared small target detection method based on improved weighted local contrast is proposed in this paper.First,the ratio information between the target and local background is utilized as an enhancement factor.The local contrast is calculated by incorporating the heterogeneity between the target and local background.Then,a local product weighted method is designed based on the spatial dissimilarity between target and background to further enhance target while suppressing background.Finally,the location of target is obtained by adaptive threshold segmentation.As experimental results demonstrate,the method shows superior performance in several evaluation metrics compared with six existing algorithms on different datasets containing targets such as unmanned aerial vehicles(UAV).

Current-Aided Multiple-AUV Cooperative Localization and Target Tracking in Anchor-Free Environments

In anchor-free environments,where no devices with known positions are available,the error growth of autonomous underwater vehicle(AUV)localization and target tracking is unbounded due to the lack of references and the accumulated errors in inertial measurements.This paper aims to improve the localization and tracking accuracy by involving current information as extra references.We first integrate current measurements and maps with belief propagation and design a distributed current-aided message-passing scheme that theoretically solves the localization and tracking problems.Based on this scheme,we propose particle-based cooperative localization and target tracking algorithms,named CaCL and CaTT,respectively.In AUV localization,CaCL uses the current measurements to correct the predicted and transmitted position information and alleviates the impact of the accumulated errors in inertial measurements.With target tracking,the current maps are applied in CaTT to modify the position prediction of the target which is calculated through historical estimates.The effectiveness and robustness of the proposed methods are validated through various simulations by comparisons with alternative methods under different trajectories and current conditions.

LOCALIZATION FOR MOBILE TARGET IN WIRELESS SENSOR NETWORKS

A precise localization for mobile target in wireless sensor networks is presented in this letter,where a geometrical relationship is explored to improve the location estimation for mobile target,in-stead of a simple centroid approach.The equations of location compensation algorithm for mobiletarget are derived based on linear trajectory prediction and sensor selective activation.The resultsbased on extensive simulation experiments show that the compensation algorithm gets better per-formance in metrics of quality of tracking and energy efficiency with the change of sensor sensing range,the ratio of sensing range and sensor activation range,and the data sampling rate than traditionalmethods,which means our proposing can achieve better quality-energy tradeoff for mobile target inwireless sensor networks.

Virtual local target method for avoiding local minimum in potential field based robot navigation

A novel robot navigation algorithm with global path generation capability is presented. Local minimum is a most intractable but is an encountered frequently problem in potential field based robot navigation.Through appointing appropriately some virtual local targets on the journey, it can be solved effectively. The key concept employed in this algorithm are the rules that govern when and how to appoint these virtual local targets. When the robot finds itself in danger of local minimum, a virtual local target is appointed to replace the global goal temporarily according to the rules. After the virtual target is reached, the robot continues on its journey by heading towards the global goal. The algorithm prevents the robot from running into local minima anymore. Simulation results showed that it is very effective in complex obstacle environments.

Constrained auxiliary particle filtering for bearings-only maneuvering target tracking

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 the1 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.

Fluorescent co-localization of PTS1 and PTS2 and its application in analysis of the gene function and the peroxisomal dynamic in Magnaporthe oryzae

The peroxisomal matrix proteins involved in many important biological metabolism pathways in eukaryotic cells are encoded by nucleal genes, synthesized in the cytoplasm and then transported into the organelles. Targeting and import of these proteins depend on their two peroxisomal targeting signals （PTS 1 and PTS2） in sequence as we have known so far. The vectors of the fluorescent fusions with PTS, i.e., green fluorescence protein （GFP）-PTS1, GFP-PTS2 and red fluorescence protein （RFP）-PTS1, were constructed and introduced into Magnaporthe oryzae Guy ll cells. Transformants containing these fusions emitted fluorescence in a punctate pattern, and the locations of the red and green fluorescence overlapped exactly in RFP-PTS 1 and GFP-PTS2 co-transformed strains. These data indicated that both PTS1 and PTS2 fusions were imported into peroxisomes. A probable higher efficiency of PTS1 machinery was revealed by comparing the fluorescence backgrotmds in GFP-PTS1 and GFP-PTS2 transformants. By introducing both RFP-PTS1 and GFP-PTS2 into Amgpex6 mutants, the involvement of MGPEX6 gene in both PTS1 and PTS2 pathways was proved. In addition, using these transformants, the inducement ofperoxisomes and the dynamic of peroxisomal number during the pre-penetration processes were investigated as well. In summary, by the localization and co-localization of PTS1 and PTS2, we provided a useful tool to evaluate the biological roles of the peroxisomes and the related genes.

ALGORITHM FOR ACOUSTIC PASSIVE LOCALIZATION WITH DUAL ARRAYS

Aiming at the problem of 3D target localization by time delay estimation, this paper proposes a new acoustic passive localization method, which can provide high precision localization estimation. The first step of the two-stage algorithm is to measure the azimuth angle and pitch angle at each single array, which can obtain high precision angle estimation but low precision range estimation. And in the second step, the location of acoustic source is calculated from the angles measured above and geometry position of the two arrays. Then the accuracy of localization estimation is discussed in theory, and the influence factors and localization error are analyzed by simulation. The simulation results validate the performance of the proposed algorithm, and show the precision of localization estimation with dual arrays is superior to single array.

UnderwaterWaste Recognition and Localization Based on Improved YOLOv5

With the continuous development of the economy and society,plastic pollution in rivers,lakes,oceans,and other bodies of water is increasingly severe,posing a serious challenge to underwater ecosystems.Effective cleaning up of underwater litter by robots relies on accurately identifying and locating the plastic waste.However,it often causes significant challenges such as noise interference,low contrast,and blurred textures in underwater optical images.A weighted fusion-based algorithm for enhancing the quality of underwater images is proposed,which combines weighted logarithmic transformations,adaptive gamma correction,improved multi-scale Retinex(MSR)algorithm,and the contrast limited adaptive histogram equalization(CLAHE)algorithm.The proposed algorithm improves brightness,contrast,and color recovery and enhances detail features resulting in better overall image quality.A network framework is proposed in this article based on the YOLOv5 model.MobileViT is used as the backbone of the network framework,detection layer is added to improve the detection capability for small targets,self-attention and mixed-attention modules are introduced to enhance the recognition capability of important features.The cross stage partial(CSP)structure is employed in the spatial pyramid pooling(SPP)section to enrich feature information,and the complete intersection over union(CIOU)loss is replaced with the focal efficient intersection over union(EIOU)loss to accelerate convergence while improving regression accuracy.Experimental results proved that the target recognition algorithm achieved a recognition accuracy of 0.913 and ensured a recognition speed of 45.56 fps/s.Subsequently,Using red,green,blue and depth(RGB-D)camera to construct a system for identifying and locating underwater plastic waste.Experiments were conducted underwater for recognition,localization,and error analysis.The experimental results demonstrate the effectiveness of the proposed method for identifying and locating underwater plastic waste,and it has good localization accuracy.

A pixel-level local contrast measure for infrared small target detection

Infrared(IR) small target detection is one of the key technologies of infrared search and track(IRST)systems. Existing methods have some limitations in detection performance, especially when the target size is irregular or the background is complex. In this paper, we propose a pixel-level local contrast measure(PLLCM), which can subdivide small targets and backgrounds at pixel level simultaneously.With pixel-level segmentation, the difference between the target and the background becomes more obvious, which helps to improve the detection performance. First, we design a multiscale sliding window to quickly extract candidate target pixels. Then, a local window based on random walker(RW) is designed for pixel-level target segmentation. After that, PLLCM incorporating probability weights and scale constraints is proposed to accurately measure local contrast and suppress various types of background interference. Finally, an adaptive threshold operation is applied to separate the target from the PLLCM enhanced map. Experimental results show that the proposed method has a higher detection rate and a lower false alarm rate than the baseline algorithms, while achieving a high speed.

A camouflage target detection method based on local minimum difference constraints

To address the problems of missing inside and incomplete edge contours in camouflaged target detection results,we propose a camouflaged moving target detection algorithm based on local minimum difference constraints(LMDC).The algorithm first uses the mean to optimize the initial background model,removes the stable background region by global comparison,and extracts the edge point set in the potential target region so that each boundary point(seed)grows along the center of the target.Finally,we define the minor difference constraints term,combine the seed path and the target space consistency,and calculate the attributes of each pixel in the potential target area to realize camouflaged moving target detection.The algorithm of this paper is verified based on a public data sofa video and test videos and compared with the five classic algorithms.The experimental results show that the proposed algorithm yields good results based on integrity,accuracy,and a number of objective evaluation indexes,and its overall performance is better than that of the compared algorithms.

MORN motifs in plant PIPKs are involved in the regulation of subcellular localization and phospholipid binding

Multiple repeats of membrane occupation and recognition nexus (MORN) motifs were detected in plant phosphatidylinositl monophosphate kinase (PIPK), a key enzyme in PI-signaling pathway. Structural analysis indicates that all the MORN motifs (with varied numbers at ranges of 7-9), which shared high homologies to those of animal ones, were located at N-terminus and sequentially arranged, except those of OsPIPK1 and AtPIPK7, in which the last MORN motif was separated others by an -100 amino-acid "island" region, revealing the presence of two kinds of MORN arrangements in plant PIPKs. Through employing a yeast-based SMET (sequence of membrane-targeting) system, the MORN motifs were shown being able to target the fusion proteins to cell plasma membrane, which were further confirmed by expression of fused MORN-GFP proteins. Further detailed analysis via deletion studies indicated the MORN motifs in OsPIPK 1, together with the 104 amino-acid "island" region are involved in the regulation of differential subcellular localization, i.e. plasma membrane or nucleus, of the fused proteins. Fat Western blot analysis of the recombinant MORN polypeptide, expressed in Escherichia coli, showed that MORN motifs could strongly bind to PA and relatively slightly to PI4P and PI(4,5)P2. These results provide informative hints on mechanisms of subcellular localization, as well as regulation of substrate binding, of plant PIPKs.

Adaptive Extended Kalman Filtering for Bearings-Only Targets Tracking Problem

An adaptive extended Kalman filtering (AEKF) is proposed for nonlinear control systems. For bearingsonly targets tracking problem, we present an adaptive extended Kalman filter which suits a nonlinear observation model and a linear dynamical model. Simulation results have shown that the adaptive extended Kalman filter for the passivetracking problem performs better than the original extended Kalman filter (EKF).

Ant colony optimization for bearings-only maneuvering target tracking in sensors network

In this paper, the problem of bearings-only maneuvering target tracking in sensors network is investigated. Two objectives are proposed and optimized by the ant colony optimization （ACO）, then two kinds of node searching strategies of the ACO algorithm are presented. On the basis of the nodes determined by the ACO algorithm, the interacting multiple models extended Kalman filter （IMMEKF） for the multi-sensor bearings-only maneuvering target tracking is introduced. Simulation results indicate that the proposed ACO algorithm performs better than the Closest Nodes method. Furthermore, the Strategy 2 of the two given strategies is preferred in terms of the requirement of real time.

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.

The accurate localization of fluorescent nanoparticle Au-Ft in nu/nu mice kidney

Au-Ft,as a green synthesized nanoparticle,is composed of a ferritin nanocage enclosing a pair of Au nanoclusters inside.Our previous study has demonstrated that Au-Ft can be an excellentfluorescent probe for whole body imaging of mice with kidney specific targeting.But,the accuratelocalization of Au-Ft in kidney is still absent.In the current study,we detected and assessed the cellular and subcellular localization of Au-Ft in renal cortex and medulla of nu/nu mice after tailvein injection by using Nuance optical system(CRi,Woburn,USA)and inForm intelligent image analysis soft ware based on single cell segmentation.We obtained the fluorescence intensity and cellular location of kidney-targeting Au-Ft probe in particular cell of renal glomerulus or renaltubules,which provided valuable proofs to clarify the mechanism of Au-Ft selective enrichment in kidney and the associated metabolic processes.

Influence of local environmental target constraints on enterprise OFDI

By collecting the environmental target constraints in the annual government work report of prefecture-level cities,this paper studies its impact on local enterprises’OFDI.The main conclusions are as follows:(1)Both direct and indirect constraints have a significant positive impact on enterprises’OFDI,and the degree of direct constraints is stronger than that of indirect constraints.(2)Environmental target constraints of local governments will affect corporate OFDI behavior by affecting production costs,local economic development level and local openness,and(3)There are regional heterogeneity and investment type heterogeneity in the impact of environmental goal constraints on corporate OFDI.The suggestions are as follows:government departments can appropriately strengthen the constraint intensity of environmental targets and formulate specific restraint rules for industries with different levels of pollution,so as to effectively make use of the technology spillover effects brought about by OFDI to promote the upgrading of domestic industrial structure.When making OFDI,enterprises should clarify the investment motivation,strengthen corporate social responsibility,and make use of technology spillover effect to promote the upgrading and development of home country industry while being beneficial to their own development.

Increasing Accumulation Level of Foreign Protein in Transgenic Plants Through Protein Targeting

Targeting of the synthesized polypeptide in the cells is an important research field in modern cell biology. Cowpea trypsin inhibitor (cpti) gene has been modified and a fusion protein gene (sck) was produced by fusing a signal peptide sequence at cpti 5' end and an endoplasm reticulum (ER) retention signal peptide at cpti3' end respectively. The signal peptide can direct the newly synthesized polypeptide into ER, while ER retention signal can make the protein retained in the ER and its derivative protein body. ELISA test indicated that the accumulation level of foreign CpTI protein in sck transgenic tobacco (Nicotiana tabacum L.) was two times higher than cpti transgenic tobaccos and some individuals were four times higher. At the same time, sck transgenic tobacco has a high resistance to Lepidoptera pest due to the increased accumulation level of foreign CpTI protein. The strategy of foreign protein targeting can be used to increase the accumulation level of foreign protein in transgenic plants and can be widely applied to other related research field in plant genetic engineering.