Algorithms executed on the radar processor system contributes to a significant performance bottleneck of the overall radar system. One key performance concern is
the latency in target detection when dealing with hard deadline systems. Research has shown software optimization as one major contributor to radar system performance
improvements. This thesis aims at software optimizations using a manual and automatic approach and analyzing the results to make informed future decisions
while working with an ARM processor system. In order to ascertain an optimized implementation, a question put forward was whether the algorithms on the ARM
processor could work with a 6-antenna implementation without a decline in the performance. However, an answer would also help project how many additional
algorithms can still be added without performance decline.
The manual optimization was done based on the quantitative analysis of the software execution time. The manual optimization approach looked at the vectorization
strategy using the NEON vector register on the ARM CPU to reimplement the initial Constant False Alarm Rate(CFAR) Detection algorithm. An additional
optimization approach was eliminating redundant loops while going through the Range Gates and Doppler filters. In order to determine the best compiler for automatic
code optimization for the radar algorithms on the ARM processor, the GCC and Clang compilers were used to compile the initial algorithms and the optimized
implementation on the radar post-processing stage.
Analysis of the optimization results showed that it is possible to run the radar post-processing algorithms on the ARM processor at the 6-antenna implementation
without system load stress. In addition, the results show an excellent headroom margin based on the defined scenario. The result analysis further revealed that the
effect of dynamic memory allocation could not be underrated in situations where performance is a significant concern. Additional statements from the result demonstrated
that the GCC and Clang compiler has their strength and weaknesses when used in the compilation. One limiting factor to note on the optimization using the
NEON register is the sample size’s effect on the optimization implementation. Although it fits into the test samples used based on the defined scenario, there might
be varying results in varying window cell size situations that might not necessarily improve the time constraints
