A coherent backprojection based approach is presented for 3D shape estimation of small debris in *** approach utilizes the fact that space debris is in high-speed spinning *** use of the modulated range envelope and D...
详细信息
A coherent backprojection based approach is presented for 3D shape estimation of small debris in *** approach utilizes the fact that space debris is in high-speed spinning *** use of the modulated range envelope and Doppler spreading,a backprojection maps the data into a three-dimensional parameter domain,and the spatial coordinates of scatterers can be extracted to reconstruct 3D *** most of recent papers on the imaging of space debris or rotating targets,the rotation from the translational motion is assumed to be neglectable,while in our approach the backprojection is combined with a Fourier transform to deal with the rotation of translational motion and full coherent accumulation can be *** approach is robust in the occurrence of serious profile overlapping and strong *** confirm its validity and good performance.
Distributed Sensor Concept - DISCO was proposed [I] for multiplication of individual sensor capabilities through non-coherent cooperative target engagement. The signalprocessing technique for DISCO is Recursive Adapt...
详细信息
ISBN:
(纸本)9780819471604
Distributed Sensor Concept - DISCO was proposed [I] for multiplication of individual sensor capabilities through non-coherent cooperative target engagement. The signalprocessing technique for DISCO is Recursive Adaptive Frame Integration of Limited data - RAFIL technique [2] that was initially proposed as a way to improve the SNR [3], reduce data rate [4] and mitigate FPA noise for IR sensors [5]. In DISCO, the RAFIL technique is used in a segmented way, when constituencies of the technique are spatially and temporally separated between individual sensors. Each sensor provides to and receives data from other sensors in the network. In this paper efficiency of DISCO is discussed for acquisition, accurate handover and track correlation of smalltargets.
This paper presents a new small target detection method using scale invariant feature. Detecting smalltargets whose sizes are varying is very important to automatic target detection in infrared search and track (IRST...
详细信息
ISBN:
(纸本)9780819471604
This paper presents a new small target detection method using scale invariant feature. Detecting smalltargets whose sizes are varying is very important to automatic target detection in infrared search and track (IRST). The conventional spatial filtering methods with fixed sized kernel show limited target detection performance for incoming targets. The scale invariant target detection can be defined as searching for maxima in the 3D (x, y, and scale) representation of an image with the Laplacian function. The scale invariant feature can detect different sizes of targets robustly. Experimental results with real FUR images show higher detection rate and lower false alarm rate than conventional methods. Furthermore, the proposed method shows very low false alarms in scan-based IR images than conventional filters.
This paper uses super-resolution methods to detect small objects in infrared image sequences from a simulated airborne platform, using image registration techniques for automatic sightline stabilisation. The scene con...
详细信息
ISBN:
(纸本)9780819471604
This paper uses super-resolution methods to detect small objects in infrared image sequences from a simulated airborne platform, using image registration techniques for automatic sightline stabilisation. The scene consists of multiple layers, corresponding to a static background scene and layers of cloud cover at varying heights. The motivation is to evaluate the performance of super-resolution methods in the presence of three-dimensional structured infrared clutter.
We consider target detection and tracking of stealthy targets. These targets can be characterized by a, strong aspect dependence leading to difficult detectability without a multi-static setup. Even in a multi-static ...
详细信息
ISBN:
(纸本)9780819471604
We consider target detection and tracking of stealthy targets. These targets can be characterized by a, strong aspect dependence leading to difficult detectability without a multi-static setup. Even in a multi-static setup only sensors in a, certain zone can detect the return signal, if the the aspect dependent return has a small bandwidth. We propose a solution based on a large number of simple sensor, as using many receivers increases the probability of detection. The sensors are simple in the sense that they only transmit binary detection results to a fusion center that has comparatively deep capabilities, and they do not need to know their own position or communicate with other sensors. We characterize the target position estimation performance using the Cramer-Rao bound and simulation results, considering uncertainty in nuisance parameters as the sensor positions or the specifics of the aspect dependence. We suggest a data collection protocol that includes locating sensors that detect the target and has low communication complexity. As a, novelty we also include information about "non-localized" sensors, as sensors which do not detect the target stay quiet to save bandwidth and energy, therefore are not known to the fusion center except via knowledge of the deployed sensor density and deployment region.
Operating in a coastal environment, with a multitude of boats of different sizes, detection of small extended targets is only one problem. A further difficulty is in discriminating detections of possible threats from ...
详细信息
ISBN:
(纸本)9780819471604
Operating in a coastal environment, with a multitude of boats of different sizes, detection of small extended targets is only one problem. A further difficulty is in discriminating detections of possible threats from alarms due to sea and coastal clutter, and from boats that are neutral for a specific operational task. Adding target features to detections allows filtering out clutter before tracking. Features can also be used to add labels resulting from a classification step. Both will help tracking by facilitating association. Labeling and information from features can be an aid to an operator, or can reduce the number of false alarms for more automatic systems. In this paper we present work on clutter reduction and classification of small extended targets from infrared and visual light imagery. Several methods for discriminating between classes of objects were examined, with an emphasis on less complex techniques, such as rules and decision trees. Similar techniques can be used to discriminate between targets and clutter, and between different classes of boats. Different features are examined that possibly allow discrimination between several classes. data recordings are used, in infrared and visual light, with a range of targets including rhibs, cabin boats and jet-skis.
small object detection with a low false alarm rate remains a challenge for automated hyperspectral detection algorithms when the background environment is cluttered. In order to approach this problem we are developing...
详细信息
ISBN:
(纸本)9780819471604
small object detection with a low false alarm rate remains a challenge for automated hyperspectral detection algorithms when the background environment is cluttered. In order to approach this problem we are developing a compact hyperspectral sensor that can be fielded from a small unmanned airborne platform. This platform is capable of flying low and slow, facilitating the collection of hyperspectral imagery that has a small ground-sample distance (GSD) and small atmospheric distortion. Using high-resolution hyperspectral imagery we simulate various ranges between the sensor and the objects of interest. This numerical study aids in analysis of the effects of stand-off distance on detection versus false alarm rates when using standard hyperspectral detection algorithms. Preliminary experimental evidence supports our simulation results.
Detection and tracking of maritime targets using skywave radar is influenced by the propagation medium, interference environment and target scenario. Acquired data display distortion, fading, non-stationarity, and het...
详细信息
ISBN:
(纸本)9781424423217
Detection and tracking of maritime targets using skywave radar is influenced by the propagation medium, interference environment and target scenario. Acquired data display distortion, fading, non-stationarity, and heterogeneity. Brief examples of data are given, then signalprocessing techniques are developed to provide robust adaptive Doppler processing, rejection of impulsive noise, improved CFAR using the Weibull distribution with robust two-parameter estimation, and a simple track-before-detect scheme for enhancing small SNR target detection performance.
Bias estimation using objects with unknown data association requires concurrent estimation of both biases and optimal data association. This report derives maximum a posteriori (MAP) data association likelihood ratios...
详细信息
ISBN:
(纸本)9780819471604
Bias estimation using objects with unknown data association requires concurrent estimation of both biases and optimal data association. This report derives maximum a posteriori (MAP) data association likelihood ratios for concurrent bias estimation and data association based on sensor-level track state estimates and their joint error covariance. Our approach is unique for two reasons. First, we include a bias prior that allows estimation of absolute sensor biases, rather than just relative biases. Second, we allow concurrent bias estimation and association for an arbitrary number of sensors. The two-sensor likelihood ratio is derived as a special case of the general M-sensor result.
An assurance region at level p, A(P=p), is an area in motion space that contains the target with assigned probability p. It is on the basis of A(P=p) that an action is taken or a decision made. Common model-based trac...
详细信息
ISBN:
(纸本)9780819471604
An assurance region at level p, A(P=p), is an area in motion space that contains the target with assigned probability p. It is on the basis of A(P=p) that an action is taken or a decision made. Common model-based trackers generate a synthetic distribution function for the kinematic state of the target. Unfortunately, this distribution is very coarse, and the resulting A(P=p) lack credibility. It is shown that a, map-enhanced, multiple model algorithm reduces the tracking, error and leads to a compact assurance region.
暂无评论