RSSI Strength Value Collection Example with Line Chart and Least Squares Analysis

In this example, we will collect RSSI strength values across a specified distance range and create a line chart using MATLAB. We will implement a least squares fitting algorithm to analyze the data points and generate a synthetic curve, which is particularly useful for smoothing signal fluctuations and identifying underlying patterns. The curve fitting approach can be implemented using MATLAB's polyfit function to calculate polynomial coefficients or the lsqcurvefit function for more complex nonlinear models. During the RSSI data collection process, we will examine how radio signal strength indicators can be utilized to estimate distance through path loss modeling, typically implemented using logarithmic distance formulas in code. Additionally, we will explore techniques for determining object direction and position using RSSI values, a critical aspect in numerous wireless applications such as indoor positioning systems. This exercise covers fundamental programming concepts including data acquisition loops, array manipulation for storing signal measurements, and visualization techniques using MATLAB's plot function with customization options for axis labels and grid displays. Through this comprehensive example, we will gain deep insights into practical applications of RSSI strength values and master essential MATLAB data analysis skills for signal processing applications.