The radar cross section is an important parameter to characterize radar target characteristics. The fluctuation of the data represents the size and shape of the target. Target RCS depends not only on radar frequency a...
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Recent advances in knowledge-aided space-time adaptive processing (KA-STAP) have resulted in significant performance improvements for ground moving target indication (GMTI) radar systems. In particular, the use of pri...
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Recent advances in knowledge-aided space-time adaptive processing (KA-STAP) have resulted in significant performance improvements for ground moving target indication (GMTI) radar systems. In particular, the use of prior knowledge including terrain, clutter discretes, and previously detected targets has been shown to be effective for mitigating the poor performance often encountered when operating in heterogeneous clutter environments. This paper provides an evaluation of KA-STAP techniques based on extensive processing of experimental data. Two major performance issues are addressed: high false alarm rates due to under-nulled clutter discretes and target cancellation due to corruption of the STAP training data by other targets in the scene. Each of these problems is demonstrated using experimental multi-channel X-band radar data. Methods for using prior knowledge to improve performance are presented and processing results using the experimental data are provided that show how KA-STAP can lead to significantly improved detection performance relative to conventional STAP processing.
Aiming at the aircraft target in visible light remote sensing image, this paper proposes a false alarm removal method for target detection under small sample training conditions. First, use data enhancement methods fo...
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Ultra-wideband MIMO radar can provide precise range and azimuth information of multiple targets and is widely applied in military, aviation, transportation, and other fields. However, the antenna radiates electromagne...
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ISBN:
(数字)9798331515669
ISBN:
(纸本)9798331515676
Ultra-wideband MIMO radar can provide precise range and azimuth information of multiple targets and is widely applied in military, aviation, transportation, and other fields. However, the antenna radiates electromagnetic energy in a specific direction, and the coverage area in azimuth is limited. Compared with targets in the antenna’s main lobe, the large-angle targets outside the antenna’s main lobe scatter weaker radar echoes. Therefore, weak targets will be overshadowed by strong targets. This paper proposes a near-field BP algorithm based on antenna radiation patterns compensation. The antenna radiation pattern was measured in the anechoic chamber. Then, digital beamforming technology was utilized to construct a gain compensation matrix achieving radar data compensation from different directions. Experimental results showed that the proposed algorithm effectively enhanced the energy of large-angle targets in multi-target scenes.
In the field of target detection, infrared small target detection(ISTD) is a critical area of research, playing a vital role in reconnaissance, guidance, and early warning systems. Existing spatial Filtering algorithm...
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ISBN:
(数字)9798331515669
ISBN:
(纸本)9798331515676
In the field of target detection, infrared small target detection(ISTD) is a critical area of research, playing a vital role in reconnaissance, guidance, and early warning systems. Existing spatial Filtering algorithms perform well in clean backgrounds; however, as these filters require manual design based on prior knowledge, they are prone to interference from complex scenes (e.g., clouds, buildings), leading to target omission. smalltargets typically exhibit blurry features and weak energy, making direct detection susceptible to interference from high-intensity areas, which may result in missed detections. To tackle these challenges, this paper presents a two-tier contrast improvement method (DLCE). First, a gradient filter group is used to enhance the signal-to-noise ratio (SNR) of the target, and then, built upon the concept of local contrast measurement (LCM), a novel intensity calculation method is developed. The new contrast window design effectively enhances the target’s SNR. Compared with existing algorithms, like MPCM (Multi-Scale Patch-based Contrast Measurement) on publicly available datasets, the proposed method more effectively enhances the target’s radiative intensity while suppressing background noise. The effectiveness of the proposed algorithm is confirmed by the simulation results.
Our capacity to transmit data off of a spacecraft to the ground station has not kept pace with rate of data generation from advanced sensors. One solution is to reduce the size of the data prior to transmission throug...
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Our capacity to transmit data off of a spacecraft to the ground station has not kept pace with rate of data generation from advanced sensors. One solution is to reduce the size of the data prior to transmission through advanced compression techniques. In this paper, software and hardware implementations of a novel data compression algorithm were used to compress overhead persistent infrared data with synthetic embedded dim targets. An image processing technique was subsequently applied to the decompressed data to recover the embedded targets within the image stack, and the signal-to-noise ratio of the detected targets were examined as a function of compression ratio. This paper examines the detection signal-to-noise ratio and relative speed-up for compression of 1200 frames of infrared data implemented in a general-purpose processor and a field-programmable gate array. The advantages of the FPGA implementation for processing efficiency were clearly shown, however, the reduced data precision had a negative impact on our ability to recover the dim target from the post compressed data.
We consider the problem of detecting targets behind walls using radar imaging technology. An image-domain based detection technique is proposed that allows to adapt to specific targets of interest. By doing so, clutte...
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ISBN:
(纸本)9781457705380
We consider the problem of detecting targets behind walls using radar imaging technology. An image-domain based detection technique is proposed that allows to adapt to specific targets of interest. By doing so, clutter as well as targets of no-interest are strongly reduced in the radar image. The proposed detector is automatic in the sense that no or only little prior knowledge on the image statistics is required. The detection procedure is detailed, including the choice of suitable optimality criteria. The evaluation of the proposed technique is performed using data collected from Through-the-Wall radar imaging experiments whereby we specifically consider on the detection of humans.
A new algorithm for signal selective tracking of the directions-of-arrival (DOAs) of multiple moving targets with an array of passive sensors is presented. A new method based on the principles of maximum likelihood es...
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A new algorithm for signal selective tracking of the directions-of-arrival (DOAs) of multiple moving targets with an array of passive sensors is presented. A new method based on the principles of maximum likelihood estimation and cyclostationarity is used to generate initial angle estimates which, in turn, are refined by a Kalman filter. Source angle dynamics are used to achieve correct data association. High performance is obtained with relatively low computational complexity.
We consider the problem of estimating range about unmanned aerial vehicle (UAV) swarm target. The main challenges are small radar cross-section (RCS) and high target density. In this paper, for better accumulation, we...
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