**6. References**


130 Applications of Digital Signal Processing

Additional, the design of calibration channel that is proposed to remove the systematic error is useful to acquire better performance for current application. A comprehensive set of noise

The system hardware consists only of MBFG, DAQ and PC. Compared with the conventional systems using counter and beat-frequency device, the system can be miniaturized and moved conveniently. As expected, system noise floor is good enough for current test requirement. The system will take measurement of wide range frequency into account in the future. Intuitive operator interface and command remotely will be design in

The authors thank Bian Yujing and Wang Danni for instructing. I would like to thank the present of the Chinese Academy of sciences scholarship and Zhu Liyuehua Scholarship for the supporting. The work has been supported by the key program of West Light Foundation of The CAS under Grant 2007YB03 and the National Nature Science Funds 61001076 and

Allan, D. W. – Daams, H.: *Picosecond Time Difference Measurement System* Proc. 29th Annual

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C. A. Greenhall, A. Kirk, and R. L. Tjoelker. *A Multi-Channel Stability Analyzer for Frequency* 

C. A. Greenhall, A. Kirk, R. L. Tjoelker. *Frequency Standards Stability Analyzer for the Deep* 

D. A. Howe, D. W. Allan, and J. A. Barnes, 1981, *Properties of signal sources and measurement* 

D.A.Howe,C.A.Greenhall.Total Variance: a Progress Report on a New Frequency Stabbility

David A, Howe. *Frequency Stability*.1703-1720, National Institute of Standards and

D.B.Sulliivan, D.W.Allan, D.A.Howe and F.L.Walls, *Characterization of Clocks and Oscillators*,

E. A. Burt, D. G. Enzer, R. T. Wang, W. A. Diener, and R. L. Tjoelker, 2006, *Sub-10-16* 

*Frequency Stability for Continuously Running Clocks: JPL's Multipole LITS Frequency Standard*s, in Proceedings of the 38th Annual Precise Time and Time Interval (PTTI)

*progress report,* in Proceedings of the 33rd Annual Precise Time and Time Interval (PTTI) Systems and Applications Meeting, 27-29 November 2001, Long Beach,

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floor tests under all conditions has not been carried out with the current system.

following work.

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**6. References** 

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**5. Acknowledgment** 

Systems and Applications Meeting, 5-7 December 2006, Reston, Virginia, USA (U.S. Naval Observatory, Washington, D.C.), 271-292.


**7** 

*Mexico* 

**High-Speed VLSI Architecture Based on** 

**Massively Parallel Processor Arrays for** 

**Real-Time Remote Sensing Applications** 

*1Mechatronic Department, Engineering School, Autonomous University of Yucatan 2Computer Engineering Dept., Mathematics School, Autonomous University of Yucatan* 

Developing computationally efficient processing techniques for massive volumes of hyperspectral data is critical for space-based Earth science and planetary exploration (see for example, (Plaza & Chang, 2008), (Henderson & Lewis, 1998) and the references therein). With the availability of remotely sensed data from different sensors of various platforms with a wide range of spatiotemporal, radiometric and spectral resolutions has made remote sensing as, perhaps, the best source of data for large scale applications and study. Applications of Remote Sensing (RS) in hydrological modelling, watershed mapping, energy and water flux estimation, fractional vegetation cover, impervious surface area mapping, urban modelling and drought predictions based on soil water index derived from remotelysensed data have been reported (Melesse et al., 2007). Also, many RS imaging applications require a response in (near) real time in areas such as target detection for military and homeland defence/security purposes, and risk prevention and response. Hyperspectral imaging is a new technique in remote sensing that generates images with hundreds of spectral bands, at different wavelength channels, for the same area on the surface of the Earth. Although in recent years several efforts have been directed toward the incorporation of parallel and distributed computing in hyperspectral image analysis, there are no standardized architectures or Very Large Scale Integration (VLSI) circuits for this purpose in

Additionally, although the existing theory offers a manifold of statistical and descriptive regularization techniques for image enhancement/reconstruction, in many RS application areas there also remain some unsolved crucial theoretical and processing problems related to the computational cost due to the recently developed complex techniques (Melesse et al., 2007), (Shkvarko, 2010), (Yang et al., 2001). These descriptive-regularization techniques are associated with the unknown statistics of random perturbations of the signals in turbulent medium, imperfect array calibration, finite dimensionality of measurements, multiplicative signal-dependent speckle noise, uncontrolled antenna vibrations and random carrier trajectory deviations in the case of Synthetic Aperture Radar (SAR) systems (Henderson & Lewis, 1998), (Barrett & Myers, 2004). Furthermore, these techniques are not suitable for

**1. Introduction** 

remote sensing applications.

A. Castillo Atoche1, J. Estrada Lopez2, P. Perez Muñoz1 and S. Soto Aguilar2

Ya Liu, Xiao-Hui Li, Yu-Lan Wang, *Multi-Channel Beat-Frequency Digital Measurement System for Frequency Standard*, 2009 IEEE International Frequency Control Symposium, 679- 684
