Adaptive Spatial/Temporal/Spectral Filters For Background Clutter Suppression And Target Detection

1982 ◽  
Vol 21 (6) ◽  
Author(s):  
C. D. Wang
Keyword(s):  
Target Detection ◽  
Clutter Suppression ◽  
Spectral Filters ◽  
Background Clutter

scholarly journals Extremely Robust Remote-Target Detection Based on Carbon Dioxide-Double Spikes in Midwave Spectral Imaging

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2896 ◽  
Author(s):  
Sungho Kim ◽  
Jungsub Shin ◽  
Joonmo Ahn ◽  
Sunho Kim
Keyword(s):  
Carbon Dioxide ◽  
Fourier Transform ◽  
Target Detection ◽  
Emission Band ◽  
Co2 Emission ◽  
Spectral Feature ◽  
Spectral Imaging ◽  
Joint Analysis ◽  
Spectral Bands ◽  
Background Clutter

Infrared ship-target detection for sea surveillance from the coast is very challenging because of strong background clutter, such as cloud and sea glint. Conventional approaches utilize either spatial or temporal information to reduce false positives. This paper proposes a completely different approach, called carbon dioxide-double spike (CO2-DS) detection in midwave spectral imaging. The proposed CO2-DS is based on the spectral feature where a hot CO2 emission band is broader than that which is absorbed by normal atmospheric CO2, which generates CO2-double spikes. A directional-mean subtraction filter (D-MSF) detects each CO2 spike, and final targets are detected by joint analysis of both types of detection. The most important property of CO2-DS detection is that it generates an extremely low number of false positive caused by background clutter. Only the hot CO2 spike of a ship plume can penetrate atmosphere, and furthermore, there are only ship CO2 plume signatures in the double spikes of different spectral bands. Experimental results using midwave Fourier transform infrared (FTIR) in a remote sea environment validate the extreme robustness of the proposed ship-target detection.

Through Wall Stationary Human Target Detection and Localization Using OFDM-UWB Radar

Frequenz ◽  
2016 ◽  
Vol 70 (5-6) ◽  
Author(s):  
Zohra Slimane ◽  
Abdelmalek Abdelhafid
Keyword(s):  
Target Detection ◽  
Wide Band ◽  
Human Being ◽  
Concrete Wall ◽  
Uwb Radar ◽  
Spectrum Density ◽  
Background Clutter ◽  
Detection And Localization ◽  
Minimum System ◽  
System Operating

AbstractThis paper focuses on through wall stationary human target detection and localization using an OFDM based Ultra-Wide Band radar (OFDM-UWB). Our investigations relate to a monostatic UWB radar operating in the band [1.99–3] GHz at central frequency 2.5 GHz and emitting a power of –22 dBm, meeting FCC UWB spectrum density requirements. The detection of a human being is possible due to respiratory movements of the chest. Using the short-term Fourier transform, along with the optimal filtering and an averaging technique for background clutter suppression, interesting information could be extracted from the recorded waveforms about the presence and position of a human being behind a 20-cm-thick concrete wall. The results of the experimental simulations under Matlab/simulink are then presented. A maximum range of 4 m was found to be possible with a minimum system operating SNR of 5 dB.

scholarly journals Low-Altitude and Slow-Speed Small Target Detection Based on Spectrum Zoom Processing

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Xuwang Zhang ◽  
Songtao Lu ◽  
Jinping Sun ◽  
Wei Shangguan
Keyword(s):  
Target Detection ◽  
Doppler Frequency ◽  
Real Data ◽  
Detection Algorithm ◽  
Clutter Suppression ◽  
Slow Speed ◽  
Small Target Detection ◽  
Ground Clutter ◽  
Radar Systems ◽  
Low Altitude

This paper proposes a spectrum zoom processing based target detection algorithm for detecting the weak echo of low-altitude and slow-speed small (LSS) targets in heavy ground clutter environments, which can be used to retrofit the existing radar systems. With the existing range-Doppler frequency images, the proposed method firstly concatenates the data from the same Doppler frequency slot of different images and then applies the spectrum zoom processing. After performing the clutter suppression, the target detection can be finally implemented. Through the theoretical analysis and real data verification, it is shown that the proposed algorithm can obtain a preferable spectrum zoom result and improve the signal-to-clutter ratio (SCR) with a very low computational load.

scholarly journals DETECTION OF SHIP TARGETS IN POLARIMETRIC SAR DATA USING 2D-PCA DATA FUSION

2015 ◽  
Vol XL-7/W3 ◽  
pp. 1017-1024
Author(s):  
C. Theoharatos ◽  
A. Makedonas ◽  
N. Fragoulis ◽  
V. Tsagaris ◽  
S. Costicoglou
Keyword(s):  
Data Fusion ◽  
Target Detection ◽  
Single Channel ◽  
False Alarms ◽  
Detection Accuracy ◽  
Constant False Alarm Rate ◽  
Additional Advantage ◽  
Detection Model ◽  
Background Clutter ◽  
Fusion Scheme

Data fusion has lately received a lot of attention as an effective technique for several target detection and classification applications in different remote sensing areas. In this work, a novel data fusion scheme for improving the detection accuracy of ship targets in polarimetric data is proposed, based on 2D principal components analysis (2D-PCA) technique. By constructing a fused image from different polarization channels, increased performance of ship target detection is achieved having higher true positive and lower false positive detection accuracy as compared to single channel detection performance. In addition, the use of 2D-PCA provides the ability to discriminate and classify objects and regions in the resulting image representation more effectively, with the additional advantage of being more computational efficient and requiring less time to determine the corresponding eigenvectors, compared to e.g. conventional PCA. Throughout our analysis, a constant false alarm rate (CFAR) detection model is applied to characterize the background clutter and discriminate ship targets based on the Weibull distribution and the calculation of local statistical moments for estimating the order statistics of the background clutter. Appropriate pre-processing and post-processing techniques are also introduced to the process chain, in order to boost ship discrimination and suppress false alarms caused by range focusing artifacts. Experimental results provided on a set of Envisat and RadarSat-2 images (dual and quad polarized respectively), demonstrate the advantage of the proposed data fusion scheme in terms of detection accuracy as opposed to single data ship detection and conventional PCA, in various sea conditions and resolutions. Further investigation of other data fusion techniques is currently in progress.

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