Estimating Atmospheric Params w/ Autocorrelation & Spectral Density Funcs.

AI Thread Summary
The discussion focuses on estimating atmospheric parameters using autocorrelation and spectral density functions in a coherent process experiment. Key questions include calculating the maximum velocity represented by the spectral density function, determining the minimum resolvable velocity, and finding the pulse length associated with a 500 m resolution using a 13-bit Barker code. Participants express uncertainty about the wavelength needed for calculations and how to derive the minimum velocity. The relationship between maximum velocity, resolution, and sampling properties of the signal is emphasized as crucial for understanding the system's performance.
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Homework Statement


An experiment probes a coherent process and the receiver is coherent. The autocorrelation function and the spectral density function are estimated and transformaed into atmospheric parameters. See Table 1 below

1) Calculate the maximum velocity (in m/s) that may be represented by the spectral density function.2) What is the minimum difference in velocity that can be resolves by this system ?3) 500 m resolution is archieved by using 13 bit Barker code. What is the pulse length ?Tabel 1.

PRF [Hz] 1200
No. of coherent
integrations 32
Resolution [m] 500
Lag resolution [ms] 24.6
Nr of bits in code 13
Maximum lag [s ] 25
Operating frequency 45

Homework Equations



v = f*λ (1)

The Attempt at a Solution



1)
How can i do this when i don't know the wavelength ? Should i suppose that the maximum velocity is the speed of light ?

2)
How can i know the minimum velocity here ?

3)
What should i do here ?

I don't know were the black lines comes from ? <Moderator's note: [s ] was interpreted as a BB code>
 
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The maximum velocity is related to the resolution and sampling properties of the signal and of the computed quantities (like PSD).
 
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