Passive target tracking with intermittent measurement based on random finite set

In the tracking problem for the maritime radiation source by a passive sensor,there are three main difficulties,i.e.,the poor observability of the radiation source,the detection uncertainty(false and missed detections)and the uncertainty of the target appearing/disappearing in the field of view.These difficulties can make the establishment or maintenance of the radiation source target track invalid.By incorporating the elevation information of the passive sensor into the automatic bearings-only tracking(BOT)and consolidating these uncertainties under the framework of random finite set(RFS),a novel approach for tracking maritime radiation source target with intermittent measurement was proposed.Under the RFS framework,the target state was represented as a set that can take on either an empty set or a singleton; meanwhile,the measurement uncertainty was modeled as a Bernoulli random finite set.Moreover,the elevation information of the sensor platform was introduced to ensure observability of passive measurements and obtain the unique target localization.Simulation experiments verify the validity of the proposed approach for tracking maritime radiation source and demonstrate the superiority of the proposed approach in comparison with the traditional integrated probabilistic data association(IPDA)method.The tracking performance under different conditions,particularly involving different existence probabilities and different appearance durations of the target,indicates that the method to solve our problem is robust and effective.

Improved particle filtering techniques based on generalized interactive genetic algorithm

This paper improves the resampling step of particle filtering（PF） based on a broad interactive genetic algorithm to resolve particle degeneration and particle shortage.For target tracking in image processing,this paper uses the information coming from the particles of the previous fame image and new observation data to self-adaptively determine the selecting range of particles in current fame image.The improved selecting operator with jam gene is used to ensure the diversity of particles in mathematics,and the absolute arithmetical crossing operator whose feasible solution space being close about crossing operation,and non-uniform mutation operator is used to capture all kinds of mutation in this paper.The result of simulating experiment shows that the algorithm of this paper has better iterative estimating capability than extended Kalman filtering（EKF）,PF,regularized partide filtering（RPF）,and genetic algorithm（GA）-PF.

Fractal detector design and application in maritime target detection

The fractal properties of sea clutter are proposed and applied to the maritime target detection. Calculation of the measured data shows that, the Hurst exponent of the sea clutter with targets and the sea clutter without targets are different, which enables us to detect low-observable targets within the sea clutter. This paper explains the reason why the Hurst exponent can distinguish the presence or absence of targets in theory and proposes a fractal detector based on the Hurst exponent. Comparing the fractal detector proposed in this paper to the energy detector by the detection results of 140 frames data of the real sea clutter, it is demonstrated that the fractal detection method has a better detection performance. In order to get systemic conclusions, the new sea clutter data with different signal-to-clutter ratios (SCRs) are constructed in the way that add the sea clutter data with targets to the pure sea clutter data. The results show that the fractal detection method has a better performance than the statistical method on detection of maritime targets, especially maritime weak targets with low SCR. © 1990-2011 Beijing Institute of Aerospace Information.

Multi-EAP: Extended EAP for multi-estimate extraction for SMC-PHD filter

The ability to extract state-estimates for each target of a multi-target posterior, referred to as multi-estimate extraction（MEE）, is an essential requirement for a multi-target filter, whose key performance assessments are based on accuracy, computational efficiency and reliability. The probability hypothesis density（PHD） filter, implemented by the sequential Monte Carlo approach,affords a computationally efficient solution to general multi-target filtering for a time-varying number of targets, but leaves no clue for optimal MEE. In this paper, new data association techniques are proposed to distinguish real measurements of targets from clutter, as well as to associate particles with measurements. The MEE problem is then formulated as a family of parallel singleestimate extraction problems, facilitating the use of the classic expected a posteriori（EAP） estimator, namely the multi-EAP（MEAP） estimator. The resulting MEAP estimator is free of iterative clustering computation, computes quickly and yields accurate and reliable estimates. Typical simulation scenarios are employed to demonstrate the superiority of the MEAP estimator over existing methods in terms of faster processing speed and better estimation accuracy.

A novel range-Doppler imaging algorithm with OFDM radar

Traditional pulse Doppler radar estimates the Doppler frequency by taking advantage of Doppler modulation over different pulses and usually it requires a few pulses to estimate the Dop- pler frequency. In this paper, a novel range-Doppler imaging algorithm based on single pulse with orthogonal frequency division multiplexing （OFDM） radar is proposed, where the OFDM pulse is composed of phase coded symbols. The Doppler frequency is estimated using one single pulse by utilizing Doppler modulation over different symbols, which remarkably increases the data update rate. Besides, it is shown that the range and Doppler estimations are completely independent and the well-known range-Doppler coupling effect does not exist. The effects of target movement on the performances of the proposed algorithm are also discussed and the results show that the algo- rithm is not sensitive to velocity. Performances of the proposed algorithm as well as comparisons with other range-Doppler algorithms are demonstrated via simulation experiments.

Coverage analysis for sensor networks based on Clifford algebra

The coverage performance is the foundation of information acquisition in distributed sensor networks. The previously proposed coverage work was mostly based on unit disk coverage model or ball coverage model in 2D or 3D space, respectively. However, most methods cannot give a homogeneous coverage model for targets with hybrid types. This paper presents a coverage analysis approach for sensor networks based on Clifford algebra and establishes a homogeneous coverage model for sensor networks with hybrid types of targets. The effectiveness of the approach is demonstrated with examples.

Difference beam aided target detection in monopulse radar

The classical detection step in a monopulse radar system is based on the sum beam only, the performance of which is not optimal when target is not at the beam center. Target detection aided by the difference beam can improve the performance at this case. However, the existing difference beam aided target detectors have the problem of performance deterioration at the beam center, which has limited their application in real systems. To solve this problem, two detectors are proposed in this paper. Assuming the monopulse ratio is known, a generalized likelihood ratio test （GLRT） detector is derived, which can be used when targeting information on target direction is available. A practical dual-stage detector is proposed for the case that the monopulse ratio is unknown. Simulation results show that performances of the proposed detectors are superior to that of the classical detector.

OGSRN:Optical-guided super-resolution network for SAR image

Although Convolutional Neural Networks(CNNs)have significantly improved the development of image Super-Resolution(SR)technology in recent years,the existing SR methods for SAR image with large scale factors have rarely been studied due to technical difficulty.A more efficient method is to obtain comprehensive information to guide the SAR image reconstruction.Indeed,the co-registered High-Resolution(HR)optical image has been successfully applied to enhance the quality of SAR image due to its discriminative characteristics.Inspired by this,we propose a novel Optical-Guided Super-Resolution Network(OGSRN)for SAR image with large scale factors.Specifically,our proposed OGSRN consists of two sub-nets:a SAR image SuperResolution U-Net(SRUN)and a SAR-to-Optical Residual Translation Network(SORTN).The whole process during training includes two stages.In stage-1,the SR SAR images are reconstructed by the SRUN.And an Enhanced Residual Attention Module(ERAM),which is comprised of the Channel Attention(CA)and Spatial Attention(SA)mechanisms,is constructed to boost the representation ability of the network.In stage-2,the output of the stage-1 and its corresponding HR SAR images are translated to optical images by the SORTN,respectively.And then the differences between SR images and HR images are computed in the optical space to obtain feedback information that can reduce the space of possible SR solution.After that,we can use the optimized SRUN to directly produce HR SAR image from Low-Resolution(LR)SAR image in the testing phase.The experimental results show that under the guidance of optical image,our OGSRN can achieve excellent performance in both quantitative assessment metrics and visual quality.

Velocity estimation of an airplane through a single satellite image

The motion information of a moving target can be recorded in a single image by a push-broom satellite.A push-broom satellite image is composed of many image lines sensed at different time instants.A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed.Some key points on the high-resolution image of the plane are chosen to determine the velocity（speed and direction）.The performance of the method is tested and verified by experiments using a WorldView-1 image.

Complex Correspondences in Straight Line Stereo Matching

Partial occlusion and fragmented lines will result in the various cases of straight line correspondences, such as one-to-one, one-to-many or many-to-many ones. However, the complex correspondences, such as one-to-many and many-to-many ones, are usually ignored or cannot be established completely in the existing methods. Here, the essence of the complex correspondences will be analyzed. Based on the two characteristics of a straight line, which are introduced by regarding a straight line as a set of collinear points, the compatibility between the complex correspondences and the uniqueness constraint of point correspondence is proved and a new uniqueness constraint of correspondence for matching lines is proposed. Based on the analysis of the complex correspondences, a new concept of line feature group is defined to describe a set of integral correspondences among straight line features from different images and then a new algorithm for establishing all the correspondences completely is described simply. The experimental results with real stereo images illustrate that the complex correspondences among straight lines are actual cases and can be established effectively.

Bernoulli particle flter with observer altitude for maritime radiation source tracking in the presence of measurement uncertainty

For maritime radiation source target tracking in particular electronic counter measures（ECM）environment,there exists two main problems which can deteriorate the tracking performance of traditional approaches.The frst problem is the poor observability of the radiation source.The second one is the measurement uncertainty which includes the uncertainty of the target appearing/disappearing and the detection uncertainty（false and missed detections）.A novel approach is proposed in this paper for tracking maritime radiation source in the presence of measurement uncertainty.To solve the poor observability of maritime radiation source target,using the radiation source motion restriction,the observer altitude information is incorporated into the bearings-only tracking（BOT）method to obtain the unique target localization.Then the two uncertainties in the ECM environment are modeled by the random fnite set（RFS）theory and the Bernoulli fltering method with the observer altitude is adopted to solve the tracking problem of maritime radiation source in such context.Simulation experiments verify the validity of the proposed approach for tracking maritime radiation source,and also demonstrate the superiority of the method compared with the traditional integrated probabilistic data association（IPDA）method.The tracking performance under different conditions,particularly those involving different duration of radiation source opening and switching-off,indicates that the method to solve our problem is robust and effective.

Three-dimensional analysis of relationship between relative orientation and motion modes

Target motion modes have a close relationship with the relative orientation of missile-totarget in three-dimensional highly maneuvering target interception. From the perspective of relationship between the sensor coordinate system and the target body coordinate system, a basic model of sensor is stated and the definition of relative angular velocity between the two coordinate systems is introduced firstly. Then, the three-dimensional analytic expressions of relative angular velocity for different motion modes are derived and simplified by analyzing the influences of target centroid motion, rotation around centroid and relative motion. Finally, the relationships of the relative angular velocity directions and values with motion modes are discussed. Simulation results validate the rationality of the theoretical analysis. It is demonstrated that there are significant differences of the relative orientation in different motion modes which include luxuriant information about motion modes. The conclusions are significant for the research of motion mode identification,maneuver detection, maneuvering target tracking and interception using target signatures.