Current radar signal processor architectures lack either performance or flexibility in terms of ease of
modification and large design time overheads. Combinations of processors and FPGAs are typically
hard-wired together into a precisely timed and pipelined solution to achieve a desired level of functionality
and performance. Such a fixed processing solution is clearly not feasible for new algorithm
evaluation or quick changes during field tests. A more flexible solution based on a high-performance
soft-core processing architecture is proposed.
To develop such a processing architecture, data and signal-flow characteristics of common radar signal
processing algorithms are analysed. Each algorithm is broken down into signal processing and
mathematical operations. The computational requirements are then evaluated using an abstract model
of computation to determine the relative importance of each mathematical operation. Critical portions
of the radar applications are identified for architecture selection and optimisation purposes.
Built around these dominant operations, a soft-core architecture model that is better matched to the
core computational requirements of a radar signal processor is proposed. The processor model is
iteratively refined based on the previous synthesis as well as code profiling results. To automate this
iterative process, a software development environment was designed. The software development environment
enables rapid architectural design space exploration through the automatic generation of development tools (assembler, linker, code editor, cycle accurate emulator / simulator, programmer,
and debugger) as well as platform independent VHDL code from an architecture description file. Together
with the board specific HDL-based HAL files, the design files are synthesised using the vendor
specific FPGA tools and practically verified on a custom high performance development board. Timing
results, functional accuracy, resource usage, profiling and performance data are analysed and fed
back into the architecture description file for further refinement.
The results from this iterative design process yielded a unique transport-based pipelined architecture.
The proposed architecture achieves high data throughput while providing the flexibility that
a software-programmable device offers. The end user can thus write custom radar algorithms in
software rather than going through a long and complex HDL-based design. The simplicity of this
architecture enables high clock frequencies, deterministic response times, and makes it easy to understand.
Furthermore, the architecture is scalable in performance and functionality for a variety of
different streaming and burst-processing related applications.
A comparison to the Texas Instruments C66x DSP core showed a decrease in clock cycles by a factor
between 10.8 and 20.9 for the identical radar application on the proposed architecture over a range of
typical operating parameters. Even with the limited clock speeds achievable on the FPGA technology,
the proposed architecture exceeds the performance of the commercial high-end DSP processor.
Further research is required on ASIC, SIMD and multi-core implementations as well as compiler
technology for the proposed architecture. A custom ASIC implementation is expected to further
improve the processing performance by factors between 10 and 27.
Dissertation (MEng)--University of Pretoria, 2014.
Broich, René; Grobler, Hans(Institute of Electrical and Electronics Engineers, 2015-01)
Current radar signal processors (RSPs) lack either
performance or flexibility. Custom soft-core processors exhibit
potential in high-performance signal processing applications,
yet remain relatively unexplored in research ...
There is currently a global increase in Eucalyptus pulpwood plantations. Harvesting systems traditionally utilised in the northern hemisphere are being used in Eucalyptus pulpwood plantations worldwide. However, the small ...
Govender, Nicolin; Wilke, Daniel Nicolas; Kok, Schalk; Els, Rosanne(Elsevier, 2014-11)
Understanding the dynamical behavior of Granular Media (GM) is extremely important to
many industrial processes. Thus simulating the dynamics of GMis critical in the design and
optimization of such processes. However, ...