Automotive radar sensors will be used in many future applications to increase comfort and safety. Compared to classical radar applications like air surveillance, the automotive radar observation area is rather small, ...
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Automotive radar sensors will be used in many future applications to increase comfort and safety. Compared to classical radar applications like air surveillance, the automotive radar observation area is rather small, but will contain numerous different targets. Due to the close distance of these objects the target resolution procedures become very important. This paper gives an overview about automotive radar signalprocessing schemes in multiple target situations.
The Tanner Research Wave Process is a moving point target detection algorithm that uses the spatio-temporal correlation of points from a target trajectory to build a large aggregate response, thereby increasing the pr...
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The Tanner Research Wave Process is a moving point target detection algorithm that uses the spatio-temporal correlation of points from a target trajectory to build a large aggregate response, thereby increasing the probability of detection for dim and low-contrast point targets moving amidst dense background and noise. The Wave Process is naturally represented as a 2-D array of linear passive analog components, with each node directly stimulated by its focal plane detector. The Wave Process can be implemented in compact, low-power hardware: analog VLSI for near-focal-plane integration, and dedicated digital for near-term applications, both with a fine-grain parallel architecture that can accommodate fast-frame-rate sensors. The Wave Process generates a real-time Region of Interest to window focal planes, reducing the data rate and sensor processing throughput requirements, thereby also reducing the overall sensor processor power, weight, and size requirements.
A monopulse radar is able to derive accurate angular measurements via intelligent processing of its sum and difference channel returns. Recently there have emerged techniques for angular estimation of several unresolv...
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ISBN:
(纸本)081945351X
A monopulse radar is able to derive accurate angular measurements via intelligent processing of its sum and difference channel returns. Recently there have emerged techniques for angular estimation of several unresolved targets. meaning targets that are. in principle, merged within the same radar beam, can be extracted separately. The key is the joint exploitation of information in several range bins. Here we show the performance of this approach in a high-fidelity simulation: we observe considerable improvement in track RMSE, but little corresponding, gain in track completeness. Coupled with a hidden Markov model on target number, however, the performance is impressive.
small target detection and classification is problematic. For targets that operate as part of a cluster, classification can be performed based on the characteristics of the cluster's operations, instead of trying ...
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ISBN:
(纸本)9781628410297
small target detection and classification is problematic. For targets that operate as part of a cluster, classification can be performed based on the characteristics of the cluster's operations, instead of trying to identify an individual cluster-member directly. This paper presents an algorithm for object identification based on comparing networks of point-to-point distances between features identified by an image feature detection algorithm. It discusses the alterations required to make the algorithm suitable for performing cluster-formation based characterization of smalltargets from point or near-point source data. An analysis of the algorithm's performance is presented and it efficacy for this application assessed.
Infrared sensors and advanced signalprocessing are used to detect small (or "point") targets in highly cluttered and noisy environments. In this paper, a wavelet detection algorithm and tracking of small ta...
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ISBN:
(纸本)0819444782
Infrared sensors and advanced signalprocessing are used to detect small (or "point") targets in highly cluttered and noisy environments. In this paper, a wavelet detection algorithm and tracking of smalltargets in clutter will be discussed. A new registration algorithm based on optical flow estimates with matched subspace detectors against small maneuverable targets is also discussed. Both detectors incorporate adaptive constant false alarm rate (CFAR) detection statistics. Simulation of the detection and tracking algorithms using an unclassified database with a helicopter target and platform for the video cameras is summarized.
Unobstructed, large RCS targets, similar radar targets surrounded by moving foliage, and smalltargets in severe clutter have been used as test cases for two pre-processing algorithms and several threshold levels in a...
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Unobstructed, large RCS targets, similar radar targets surrounded by moving foliage, and smalltargets in severe clutter have been used as test cases for two pre-processing algorithms and several threshold levels in an experimental millimeter wave radar system. The rather conventional "six-out-of-eight" pulse radar selection method with binary output has been compared to an algorithm that accepts a target. if the pre-defined trigger level is crossed by the average of the eight consecutive pulses. In this case, however, the output is an analog value corresponding to the relative average video amplitude. In terms of plotted video, this process seems to give a slightly better combination of false alarm rate and detection probability. Large targets are easier to detect from foliage clutter with the conventional method.
In this paper we look at various algorithms for approximating the target-measurement association probabilities of the Joint Probabilistic data Association Filter (JPDAF). We consider their computational complexity and...
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ISBN:
(纸本)9780819481627
In this paper we look at various algorithms for approximating the target-measurement association probabilities of the Joint Probabilistic data Association Filter (JPDAF). We consider their computational complexity and compare their performance with respect to the Mean Optimal Subpattern Assignment (MOSPA) statistic in a scenario involving closely-spaced targets.
This paper presents a research development of wavelets feature aided tracking, which effectively combines information from both high-resolution range (HRR) radar profiles and ground moving target indication (GMTI) rad...
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This paper presents a research development of wavelets feature aided tracking, which effectively combines information from both high-resolution range (HRR) radar profiles and ground moving target indication (GMTI) radar reports. The state-of-the-art wavelets-based statistical signalprocessing technique: wavelets domain hidden Markov trees is used to extract robust features from HRR profiles. With the assistance of HRR wavelets features, a GMTI tracker based on a probabilistic data association logic can effectively track ground moving targets in confusing scenarios. (C) 2003 Elsevier B.V. All rights reserved.
This paper analyzes a new method to detect targets. The new method, called `super noncoherent integration' (SNCI), can improve overall detection performance by typically 5 dB to 10 dB relative to conventional nonc...
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ISBN:
(纸本)0819415391
This paper analyzes a new method to detect targets. The new method, called `super noncoherent integration' (SNCI), can improve overall detection performance by typically 5 dB to 10 dB relative to conventional noncoherent integration. A simple back-of-the-envelope formula is derived which quantifies the performance improvement of SNCI. Conventional noncoherent integration (CNCI) uses only amplitude measurements to distinguish targets from noise or clutter. In contrast, SNCI uses amplitude data in addition to: monopulse data, quadrature monopulse data, range and Doppler data over a sequence of N transmitted radar waveforms.
A time reversal optical tomography (TROT) method for near-infrared (NIR) diffuse optical imaging of targets embedded in a highly scattering turbid medium is presented. TROT combines the basic symmetry of time reversal...
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A time reversal optical tomography (TROT) method for near-infrared (NIR) diffuse optical imaging of targets embedded in a highly scattering turbid medium is presented. TROT combines the basic symmetry of time reversal invariance and subspace-based signalprocessing for retrieval of target location. The efficacy of TROT is tested using simulated data and data obtained from NIR imaging experiments on absorptive and scattering targets embedded in Intralipid-20% suspension in water, as turbid medium. The results demonstrate the potential of TROT for detecting and locating smalltargets in a turbid medium, such as, breast tumors in early stages of growth. (C) 2011 Optical Society of America
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