Signature Adaptive Mine Detection at a Constant False Alarm Rate
نویسندگان
چکیده
A constant false alarm rate (CFAR) algorithm has been developed for use in multi-band mine detection. While it is often difficult to predict the spectral signatures of targets, the shape of the target may be known. This test exploits geometric target features and spectral differences between the target and the surrounding area. The algorithm is derived from a general statistical model of the data, which allows it to adapt to changing backgrounds and variable target signatures.
منابع مشابه
Constant False Alarm Rate Detectors in Intensive Noise Environment Conditions
A different technique of CFAR detectors procedure for moving target detection in noise environment conditions with a Poisson distributed flow and Raleigh amplitude distribution is proposed in this paper . The expressions of the detection and false alarm probability are derived for a highly fluctuating Swerling II target. A comparative analysis of the performance of different radar detectors str...
متن کاملHough Detector Threshold Analysis in the Presence of a Randomly Arriving Impulse Interference
In this paper a technique of Hough detector threshold procedure for moving target detection under conditions of randomly arriving impulse interference with a Poisson distributed flow and Raleigh amplitude distribution is proposed. The expressions of detection and false alarm probability are derived for a highly fluctuating Swerling II target. A comparative analysis of the performance of a Hough...
متن کاملBOAT−GENERATED ACOUSTIC TARGET SIGNAL DETECTION BY USE OF AN ADAPTIVE MEDIAN CFAR AND MULTI−FRAME INTEGRATION ALGORITHM (MonPmOR10)
In this paper, an Adaptive Median Constant False Alarm Rate (AMCFAR) and multi−frame post detection integration algorithm is proposed for effective real time automatic target detection of boat−generated acoustic signals, in which, an observation space is created by sampling and dividing input analog acoustic signal into multiple frames and each frame is transformed into the frequency domain. In...
متن کاملAdaptive Signal Detection in Auto-Regressive Interference with Gaussian Spectrum
A detector for the case of a radar target with known Doppler and unknown complex amplitude in complex Gaussian noise with unknown parameters has been derived. The detector assumes that the noise is an Auto-Regressive (AR) process with Gaussian autocorrelation function which is a suitable model for ground clutter in most scenarios involving airborne radars. The detector estimates the unknown...
متن کاملDetection of Saccadic Eye Movements Using the Order Statistic Constant False Alarm Rate Technique
A saccade detection method built upon the order statistic constant false alarm rate technique was applied to the detection of saccadic eye movements from electrooculographic signals. The technique is based on the adaptive thresholding approach, in which the sensitivity of the detector is adjusted according to the observed signal in order to achieve a constant false alarm rate. The investigated ...
متن کامل