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Development Of Analysis Software for LAMP System. Internal Guide Mr.G.Karunakar Associate Professor GIT, GITAM UNIVERSITY Visakhapatnam-45. External Guide Mr.Y.Bhavani Kumar Scientist/Engineer-‘SE’ NARL, Gadanki Tirupati. Introduction. Atmosphere Atmospheric Measurements
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Development Of Analysis Software for LAMP System Internal Guide Mr.G.Karunakar Associate Professor GIT, GITAM UNIVERSITY Visakhapatnam-45. External Guide Mr.Y.Bhavani Kumar Scientist/Engineer-‘SE’ NARL, Gadanki Tirupati.
Introduction • Atmosphere • Atmospheric Measurements i. In-situ measurements ii. Remote sensing observations • Concept of remote sensing i. Passive Remote sensing ii. Active Remote sensing • Introduction to Lidar
Basic Principles LIDAR – Light Detection and Ranging LIDAR is optical analogue to RADAR Similar principle to RADAR – pulses of light emitted into the atmosphere and scattered back by clouds, aerosols or air molecules Light collected by a telescope Spectrometers or interference filters isolate wavelength concerned Time-of-flight gives scattering height
Applications Cloud Geometry Aerosol Studies Boundary Layer Studies Water vapour Minor constituents e.g. ozone, hydrocarbons Temperature Wind (by Doppler-shifting) etc…
Objective Primary objectives of this project are: Analyzing the work done using the Ground based Monostatic LAMP (Lidar for Atmospheric Measurement and Probing) system. Extracting data from the output binary file. Development of different algorithms to determine various parameters of the atmospheric constituents and their variations with respect to temperature. Development of Analysis Software using user-friendly MATLAB codes for scientific application purpose.
Transmitter Section Laser: Short pulses with lengths of few nsec and Specific Spectral properties are generated by Laser. Beam Expander: To reduce the divergence of light beam before it is sent into the atmosphere. Steering Mirror: Laser beam is made to fall on the mirror. Control Unit: Microprocessor based system providing hardware interface.
Receiver Section Telescope:Collects the photons backscattered from the atmosphere followed by an optical analyzer. Detector: Received signal is converted into an electrical signal. Generally the detector can be PMT. Interference Filter: To reduce background light.
Data acquisition & Signal Processing Head on type photomultiplier tube operate in photon counting mode Pulse discriminator amplifier comparator Pulse Shaper Pulse counter Dwell time control Sweep channel analyzer memory Back Scattered photons Laser pulse trigger Photon count profile
Transmitter Specifications Laser : Diode Pumped Q Switched Nd:YAG Laser Operating Wavelength : 532nm. Output energy Per Pulse : 2 to 25Microjoules Pulse Repetition Frequency : 2500Hz Beam Divergence : <1.5mrad. Pulse Width : 2nsec.
Receiver Specifications Telescope : Schmidt Cassegrain Type. Diameter : 150mm. Field of view : 400mrad. IF filter Bandwidth(FWHM) : 0.5nm Telescope F-ratio : 9
PMT Specifications Quantum Efficiency : <10% Gain : 2.5*10^7 Data Acquisition System Specifications Type : Single Photon Counting Maximum Counting Rate : 150MHz Dwell Time : 100 to 1300ns
Raw Photon Count Data Noise Removed Signal Range Squared Signal Algorithm For LAMP Data Analysis
Plot of Range, Time, RCS Determine Duration of Cloud Average corresponding RCS w.r.t Range Plot Range vs Avg. RCS Algorithm For Cloud Base and Cloud Top
Boundary Layer Detection Techniques • Gradient Method:Mostly used to find boundary layer top. Gradient= Disadvantage: this method strongly suffers from noise. 2. Wavelet Covarience Transform:
Temporal Variation Of The Boundary Layer From Time To Time Using WCT
Raw Data Noise Corrected Data Range Corrected Data Range Normalization Number Density Calculation Estimating Back Scatter CrossSection Attenuated Back Scatter Coefficient Data Inversion Algorithm(Klett Method)
Conclusion The functioning of the currently working LAMP system was observed. Various atmospheric parameters have been derived and plotted using MATLAB user-friendly software codes. The code has been tested under different atmospheric conditions for retrieving the signal information. The developed code has the potential to apply the code for different lidar systems with minimal changes to the program.
Future Work • This work can be extended in several ways by developing the software further, by using different algorithms. • Those include the determination of timely variation of the cloud base with respect to time, determination of extinction coefficient and aerosol optical thickness values by further analyzing the klett method, comparison of variation of night time AOT values and day time AOT values etc. • In case of clouds, the scattering parameters can be determined by using klett forward or backward algorithm methods. • With the addition of these features to the developed software, by using different algorithms make it more efficient and reliable software for atmospheric observations.
Lidar Range-Resolved Optical Remote Sensing of the Atmosphere, by Claus Weitkamp, 2004. Elastic Lidar by Vladimir Kovalev, William E.Eichinger. Laser Remote Sensing by Takashi Fujii, 2005. Laser Remote Sensing Fundamentals and Applications, by Raymond M.Measures,1992. Technology Development for Atmospheric Research & Applications, by B.Manikiam, T.G.K.Murthy, Atmospheric Science programme, ISRO, june 2008. Portable Lidar system for atmospheric boundary layer Measurements, Author: Mr.Yellapragada Bhavani Kumar, Optical Engineering 45(7),1(July 2006). Resonance Lidar system for mesospheric Sodium measurements, Authors: Mr.Y.Bhavani Kumar, Mr.D.Narayana Rao, Mr.M.Sundara Murthy, Mr.M.Krishnaiah, Optical Engineering 46(8),086203(August 2007). Getting Started with MATLAB 7, A Quick introduction to Scientists and Engineers, Rudra Pratap, Eight edition, 2008. References