Ship detection and tracking using multi-frequency HFSWR
نویسندگان
چکیده
منابع مشابه
Ship Detection Using Polarimetric Radarsat-2 Data and Multi-dimensional Coherent Time-frequency Analysis
A polarimetric coherent Time-Frequency (TF) decomposition approach for ship detection is proposed in this paper. At first, the PolSAR data are decomposed in azimuth direction, range direction only or in both directions. Then a novel statistical descriptor called polarimetric TF coherence indicator, is applied to detect maritime targets in different environments. By using polarimetric RadarSat2 ...
متن کاملHigh Resolution MIMO-HFSWR Radar Using Sparse Frequency Waveforms
In high frequency surface wave radar (HFSWR) applications, range and azimuth resolutions are usually limited by the bandwidth of waveforms and the physical dimension of the radar aperture, respectively. In this paper, we propose a concept of multiple-input multiple-output (MIMO) HFSWR system with widely separated antennas transmitting and receiving sparse frequency waveforms. The proposed syste...
متن کاملTraffic Surveillance using Multi-Camera Detection and Multi-Target Tracking
Non-intrusive video-detection for traffic flow observation and surveillance is the primary alternative to conventional inductive loop detectors. Video Image Detection Systems (VIDS) can derive traffic parameters by means of image processing and pattern recognition methods. Existing VIDS emulate the inductive loops. We propose a trajectory based recognition algorithm to expand the common approac...
متن کاملHF Radar WERA Application for Ship Detection and Tracking
18 High-Frequency (HF) radars are operated in the 3-30 MHz frequency band and are known to cover ranges up to several hundred kilometers. Low power HF radar systems have been developed especially for oceanographic applications. They use electromagnetic surface wave propagation along the salty ocean. The WERA HF radar system transmits an average power of 30 watts but it achieves detection ranges...
متن کاملMulti-class Multi-object Tracking Using Changing Point Detection
This paper presents a robust multi-class multi-object tracking (MCMOT) formulated by a Bayesian filtering framework. Multiobject tracking for unlimited object classes is conducted by combining detection responses and changing point detection (CPD) algorithm. The CPD model is used to observe abrupt or abnormal changes due to a drift and an occlusion based spatiotemporal characteristics of track ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEICE Electronics Express
سال: 2010
ISSN: 1349-2543
DOI: 10.1587/elex.7.410