[PDF] Top 20 Automatic Target Recognition (ATR) System using Recurrent Neural Network (RNN) for Pulse Radar

... of target from radar return ...using pulse radar ...as radar return, either a huge number of samples is required, or the data must first be reduced by the extraction of a relatively ... See full document

... high-resolution target detection of artificial aperture microwave radar (SAR) pictures, a replacement two-stage target detection technique supported variance weighted data entropy is projected during ... See full document

... (HRRP)-based radar automatic target recognition ...the target recognition with outlier rejection task ...both recognition and rejection ... See full document

... This paper provides strong evidence that the JEM signature can be applied to ATR to identify jets. However, it should not be used alone, but used with other features such as 2D ISAR image. When the aircraft closes ... See full document

... moving radar targets introduce signal modulations known as micro-Doppler (m-D) [Chen ...the target time-frequency radar response in order to classify and identify the target [Molchanov (2012), ... See full document

... in target detection of optical and medical pictures, however increasing speckle noise for the most part interferes with its use in synthetic aperture microwave radar (SAR) ...for target detection in ... See full document

... aperture radar (SAR) automatic target recognition (ATR) is playing a very important role in military and civil ...Thus recognition using multiple classifiers fusion (MCF) has become a ... See full document

... each radar can provide their pulse parameters such as timing to their clusterhead radar, and the clusterhead radar can combine the echos (RF returns) from the target and ...the ... See full document

... aperture radar is becoming a very useful sensor for earth remote sensing ...of radar images reconstruction have significantly increased the overwhelming amount of radar ...aperture radar ... See full document

... their sensing resolutions were generally relatively limited. Yu Guo, Usman Mahmood, Zhong et al. [7–9] used deep learning/SVM classification based on privileged informa- tion or fourth-order cumulant to improve ... See full document

... in radar automatic target recognition ...on radar HRRP databases indicate that, compared with some classical kernel-based methods, the proposed MKFD-LDA not only performs better and ... See full document

... aperture radar automatic target recognition (SAR ATR), called generalized neighbor discriminant embedding ...better recognition performance than PCA and ... See full document

... Abstract. Deep convolutional neural networks (CNN) have recently proven extremely competitive in challenging visible light image and speech recognition tasks. The goal of the present study is to explore the ... See full document

... The so-called stripmap SAR acquisition geometry, illustrated in Fig. 1, is widely used. This acquisition geometry provides data along a terrain strip parallel to the flight direction (azimuth direction). The ... See full document

... the target is not reconstructed in 3D), the MBT will occupy the center of subsequent images as the UAV moves and thus the target will be reconstructed at some ... See full document

... A matched filter is designed to maximise the response of a linear system to particular known signal. Fig. 2.9 shows the basic block diagram of a matched filter radar system. The transmitted waveform is generated by ... See full document

... The LBP operator was proposed by Ojala et al. in [21], which is based on the so-called texture unit (TU) intro- duced by Wang and He in [22]. LBP has been proved a robust and computationally simple approach to describe ... See full document

... new radar HRRP target recognition method is presented via a truncated stick-breaking hidden Markov model ...the target-dependent states information are shared among multiple ... See full document

... The impacts to the measurements derived from measuring to a 360 degree prism using ATR technology for alignment was found to be significantly affected by the vertical angle of the observation. This was concluded to be a ... See full document

... Terminological variation is an integral part of the linguistic ability to realise a concept in many ways, but it is typically considered an obstacle to automatic term recognition (ATR) and term management. ... See full document