LI Implementation: Complete!

I have finished implementing the LI estimator. I added noise in the form of additive zero-mean Gaussian noise with an adjustable variance. Here are some reports from MATLAB:

 
 

Report 1

Injected Gaussian Noise with mean=0 and variance=0.001

Final Estimate=[5.5941,3.7294,4.1864]

Source Location=[5.5909,3.728,4.1865]

Bias=1.2495e-005

Report 2

Injected Gaussian Noise with mean=0 and variance=0.01

Final Estimate=[5.1913,4.0379,2.1349]

Source Location=[5.0773,4.2012,2.0265]

Bias=0.051423

 
 

A closer look shows all points of closest intersection, the actual location of the source, and our final estimate.

This marks the end of my work exploring centralized methods. I now turn my attention to distributive sensor networks. Stay tuned!