Due to its unique geographical location and regional climate, the Yellow River and its tributaries are prone to ice jams almost every spring. Ice jams can cause levees to burst, leading to severe flooding, property damage, and human casualties. Hence, there is an urgent need to carry out observations of ice conditions and make risk assessments of ice jam occurrence. Field observation is the most reliable technique, but it is usually too expensive and time-consuming, which has led to the evaluation of applied remote sensing for data capture and analysis. Owing to the factors of timeliness, image resolution, human safety, and cost, satellite or manned aerial remote sensing cannot fully meet the requirements of ice condition observation. An unmanned aerial vehicle (UAV) remote sensing system is proposed for the collection of river ice imagery, providing the benefits of low cost, flexible launch and landing logistics, safety, and appropriate hyperspatial image resolution. One Inner Mongolian segment of the Yellow River was chosen as a test area to demonstrate key technologies and specific procedures of observation and assessment of ice conditions using the UAV system. The specific UAV remote sensing system and its components are introduced along with the procedures of UAV operation and imagery acquisition. Image preprocessing techniques and ice information extraction are described in detail followed by analysis and risk assessment of the ice conditions based on the resulting panoramic imagery. Results prove the feasibility and effectiveness of applying the fixed-wing UAV system to rapid observation and risk assessment of ice jam formation over the Yellow River under harsh weather conditions including low temperatures and strong winds.
In this paper we introduce a new chaotic stream cipher Mmohocc which utilizes the
fundamental chaos characteristics. The designs of the major components of the cipher are
given. Its cryptographic properties of period, auto- and cross-correlations, and the
mixture of Markov processes and spatiotemporal effects are investigated. The cipher is
resistant to the related-key-IV, Time/Memory/Data tradeoff, algebraic, and chosen-text
attacks. The keystreams successfully passed two batteries of statistical tests and the
encryption speed is comparable with RC4.
KEYWORDS: Synthetic aperture radar, Signal processing, Signal attenuation, Signal to noise ratio, Filtering (signal processing), Interference (communication), Doppler effect, Detection theory, Data processing, Image quality
Generally the pulse repetition frequency in airborne SAR system is much higher than signal bandwidth to guarantee the maximum slant range requested. In order to reduce the large processing amount caused by high PRF, we always preprocess the echo signal in azimuth before the whole processing procedure. The conventional method is pre-filtering, which has some approximation and relatively large computation amount. This paper mainly studies pre-accumulation as another preprocessing method with relatively small computation amount. On the basis of SAR signal processing theory, we analyze and simulate the result of direct accumulation of incoherent signal in azimuth, as well as the phase loss caused by incoherence and the factors affecting the phase loss. Furthermore, present a resolution to eliminate the phase loss, which adjusting signal phase by multiplying phase difference before accumulating, and compare the computation amount with that of pre-filtering. After that, point out the condition suitable to use this method. Finally, we apply this method to raw data processing of airborne SAR and the result shows that the proposed method can achieve the image result with the similar quality to that of original processing, while reduce the computation amount considerably.
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