# Interference Mitigation for GNSS Receivers Using FFT Excision Filtering Implemented on an FPGA
## 5 Results
### Validation Results and Discussion
However, this difference between the MATLAB results and VHDL results does not affect the performance of the desired navigation and tracking loops as the Xilinx FFT model results were tested to obtain the value of \((C/No)\). The mean was \(\sim\)40 dB, which is sufficient for GNSS receiver operations. The float-point design gives the most matched results with the MATLAB simulation software with the largest amount of hardware resources. Figure 26 shows the relationship between the fixed-point design with 16-bit precision, fixed-point design with 22-bit precision, and float-point design using the Xilinx FFT model and MATLAB software simulation. It illustrates that the float-point design has a better  
Figure 24: Frequency spectrum of VHDL implementation (fixed-point with 22-precision). Figure 25: Frequency spectrum of VHDL implementation (float-point with 32-precision). performance than the fixed-point design according to \((C/No)\). Additionally, the float-point design using the Xilinx FFT model has a similar performance to the MATLAB simulation. The blue line of the float-point design starts to fall when \((J/No)\) is equal to 70 dB-Hz to reach 39 dB-Hz of \((C/No)\). In contrast, the fixed-point design with 16-bits sharply decreases to less than 35 dB-Hz of \((C/No)\) once \((J/No)\) reaches 80 dB-Hz. The fixed-point design with 22-bits shows a better performance than the fixed-point design with 16-bits. The fixed-point with 22-bits has a \((C/No)\) value equal to 28 dB-Hz when \((J/No)\) reaches 90 dB-Hz. The fixed-point with 16-bits reaches a \((C/No)\) value equal to 26 dB-Hz when the \((J/No)\) value is equal to 90 dB-Hz. The float-point design consumes more hardware resources than the fixed-point design due to the nature of the float-point length and mathematical operations. The performance of the filtered algorithm drops dramatically below the fixed-point design with 16-bits while the fixed-point design with 22-bits shows a better performance compared to other precisions of FFT. Therefore, the fixed-point with 22-bits design was chosen as a compromised solution as it achieved the desired performance using the required hardware resources compared to the float-point design. This standard of performance is significant for GNSS receiver operations such as acquisition, tracking, and navigation. These operations require a reliable, accurate, and robust performance due to their critical jobs. For this reason, the fixed-point design with 22-bits was chosen as the optimal solution for hardware implementation, trading off the desired performance against the required hardware resources. A complete \((C/No)\) comparison is shown in Table 3. The \((C/No)\) comparison confirms that the fixed-point 22-bit showed the best performance compared to the fixed-point 16-bit. Moreover, the hardware implementation using the fixed-point 22-bit showed a similar result to the MATLAB software simulation. A comparison of the utilization percentage of the hardware design resources between the fixed-point design (22-bit) and the float-point design (32-bit) is shown in Table 4. The comparison clearly shows that the float-point design consumed more hardware resources than the fixed-point design. Figure 20:0 C/No versus \(J/No\) for the float-point design, fixed-point 16-bit design, fixed-point 22-bit design, and MATLAB simulation with a single CW jammer at \(J/No=80\) dB-Hz and freqj = 6.5033 MHz.