How can I represent this expression as a Fourier Transform?

In summary, the author is researching how to represent an object in terms of a Fourier transform and believes that a constant, Gamma, is required. He is looking for a source of information on this topic and recommends reading standard radar books.
  • #1
Xyius
508
4
Hello,

I hope I am posting this in the correct forum topic. It really is more of a "mathy" type of question, but I am posting it here because it deals with radar, and this type of math is used a lot in radar. To the mods, feel free to move it to a more suitable location if desired.

I have come across an expression in my research that I believe can be represented in terms of a Fourier transform. My research is a theoretical investigation on the effectiveness of a quantum radar to see a target in relation to a normal radar. A quantum radar is a new (theoretical only at the moment) concept to use quantum states of photons to detect targets at a distance. The expression is,

[tex]\sigma = \gamma \left| \sum_{n=1}^{N} e^{i k \Delta R_n} \right|^2 [/tex]

Where ##\gamma## is a constant, ##k## is the wave number and ##\Delta R_n = \sqrt{(x-x_n)^2+(y-y_n)^2+(z-z_n)^2}##, which is the distance from the receiver (monostatic) to each atom. Basically what this expression is, is the summation of the photon wave function from each atom in the object. So ##N## represents the total number of atoms. This summation can absolutely be changed to be a continuous integral to obtain the desired result easier. However for simulation purposes for arbitrary objects, the summation form is what is required.

This problem seems to be identical to topics done in radar where an object is represented as a summation of isotropic point scatterers. Would anyone have a recommendation on where would be a good source to read up on this problem, or perhaps show me how to do the transform?
 
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  • #2

Related to How can I represent this expression as a Fourier Transform?

1. How do I determine the frequency components of a signal using Fourier Transform?

The frequency components of a signal can be determined using Fourier Transform by taking the Fourier Transform of the signal and then analyzing the magnitude and phase of the resulting frequency spectrum.

2. Can Fourier Transform be used to represent any type of signal?

Yes, Fourier Transform can be used to represent any type of signal, as long as it is finite and continuous. It is a general mathematical tool for analyzing signals and can be applied to a wide range of applications in science and engineering.

3. What is the relationship between time and frequency domains in Fourier Transform?

The relationship between time and frequency domains in Fourier Transform is that the time domain represents a signal in the time or spatial domain, while the frequency domain represents the same signal in the frequency or spectral domain. This allows for the analysis of a signal in both the time and frequency domains.

4. How does the sampling rate affect the Fourier Transform of a signal?

The sampling rate of a signal affects the Fourier Transform by determining the resolution of the frequency spectrum. A higher sampling rate will result in a more detailed frequency spectrum, while a lower sampling rate will result in a less detailed frequency spectrum.

5. Can the Fourier Transform be used for signal processing?

Yes, the Fourier Transform is commonly used for signal processing tasks such as filtering, noise reduction, and feature extraction. By analyzing the frequency components of a signal, it can be manipulated and processed in various ways to achieve the desired outcome.

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