Скачать или смотреть Performance Analysis of Range and Angle Estimation on FPGA

Step 1: Read Binary Data in MATLAB

Assuming your binary data is stored in a .bin file, you can use the fread function to read the binary data.

Step 2: Apply Algorithm in MATLAB

We apply the algorithm to process the binary data and obtain the desired results (angle and range).

We have a uniform linear array (ULA) of sensors and if you want to estimate the angle of arrival (AOA) of a signal, you can use the MUSIC algorithm.

Step 3: Translate MATLAB Algorithm to Verilog

We will need to convert the algorithm from MATLAB to Verilog. The specific details will depend on the complexity of your algorithm. For simple operations, you might directly translate them into Verilog. For more complex algorithms, you may want to use tools like MATLAB HDL Coder to generate Verilog code from MATLAB.

Step 4: Display Verilog Code on Board

We copy the Verilog code generated in Step 3 to your hardware board. This typically involves using tools provided by the board manufacturer to load and execute the Verilog code on the FPGA or ASIC.

Step 5: Display Verilog Results on the Board

After running the Verilog code on the board, your board should output the results. Make sure your board is set up to display or transmit the results, and that you have the necessary tools to capture or visualize them.

Note: - We are not having any Board so we will skip step 5.
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