REAL-TIME ADAPTIVE PULSE COMPRESSION ON RECONFIGURABLE, SYSTEM-ON-CHIP (SOC) PLATFORMS

New radar applications need to perform complex algorithms and process a large quantity of data to generate useful information for the users. This situation has motivated the search for better processing solutions that include low-power high-performance processors, efficient algorithms, and high-speed interfaces. In this work, hardware implementation of adaptive pulse compression algorithms for real-time transceiver optimization is presented, and is based on a System-on-Chip architecture for reconfigurable hardware devices. This study also evaluates the performance of dedicated coprocessors as hardware accelerator units to speed up and improve the computation of computing-intensive tasks such matrix multiplication and matrix inversion, which are essential units to solve the covariance matrix. The tradeoffs between latency and hardware utilization are also presented. Moreover, the system architecture takes advantage of the embedded processor, which is interconnected with the logic resources through high-performance buses, to perform floating-point operations, control the processing blocks, and communicate with an external PC through a customized software interface. The overall system functionality is demonstrated and tested for real-time operations using a Ku-band testbed together with a low-cost channel emulator for different types of waveforms

Pipelining Of Double Precision Floating Point Division And Square Root Operations On Field-programmable Gate Arrays

Many space applications, such as vision-based systems, synthetic aperture radar, and radar altimetry rely increasingly on high data rate DSP algorithms. These algorithms use double precision floating point arithmetic operations. While most DSP applications can be executed on DSP processors, the DSP numerical requirements of these new space applications surpass by far the numerical capabilities of many current DSP processors. Since the tradition in DSP processing has been to use fixed point number representation, only recently have DSP processors begun to incorporate floating point arithmetic units, even though most of these units handle only single precision floating point addition/subtraction, multiplication, and occasionally division. While DSP processors are slowly evolving to meet the numerical requirements of newer space applications, FPGA densities have rapidly increased to parallel and surpass even the gate densities of many DSP processors and commodity CPUs. This makes them attractive platforms to implement compute-intensive DSP computations. Even in the presence of this clear advantage on the side of FPGAs, few attempts have been made to examine how wide precision floating point arithmetic, particularly division and square root operations, can perform on FPGAs to support these compute-intensive DSP applications. In this context, this thesis presents the sequential and pipelined designs of IEEE-754 compliant double floating point division and square root operations based on low radix digit recurrence algorithms. FPGA implementations of these algorithms have the advantage of being easily testable. In particular, the pipelined designs are synthesized based on careful partial and full unrolling of the iterations in the digit recurrence algorithms. In the overall, the implementations of the sequential and pipelined designs are common-denominator implementations which do not use any performance-enhancing embedded components such as multipliers and block memory. As these implementations exploit exclusively the fine-grain reconfigurable resources of Virtex FPGAs, they are easily portable to other FPGAs with similar reconfigurable fabrics without any major modifications. The pipelined designs of these two operations are evaluated in terms of area, throughput, and dynamic power consumption as a function of pipeline depth. Pipelining experiments reveal that the area overhead tends to remain constant regardless of the degree of pipelining to which the design is submitted, while the throughput increases with pipeline depth. In addition, these experiments reveal that pipelining reduces power considerably in shallow pipelines. Pipelining further these designs does not necessarily lead to significant power reduction. By partitioning these designs into deeper pipelines, these designs can reach throughputs close to the 100 MFLOPS mark by consuming a modest 1% to 8% of the reconfigurable fabric within a Virtex-II XC2VX000 (e.g., XC2V1000 or XC2V6000) FPGA

Development and implementation of an adaptive digital beamforming network for satellite communication systems

The use of adaptive digital beamforming techniques has, until recently, been largely restricted to high performance military radar systems. Recent advances in digital technology, however, have enabled the design of single chip digital beamforming networks. This, coupled with advances in digital signal processor technology, enables complete beamforming systems to be constructed at a lower cost, thus making the application of these techniques to commercial communications systems attractive. The design and development of such an adaptative digital beamforming network are described. The system is being developed as a proof of concept laboratory based demonstrator to enable the feasibility of adaptive digital beamforming techniques for communication systems to be determined. Ultimately, digital beamforming could be used in conjunction with large array antennas for communication satellite systems. This will enable the simultaneous steering of high gain antenna beams in the direction of gr...Peer ReviewedPostprint (published version

The development of a node for a hardware reconfigurable parallel processor

This dissertation concerns the design and implementation of a node for a hardware reconfigurable parallel processor. The hardware that was developed allows for the further development of a parallel processor with configurable hardware acceleration. Each node in the system has a standard microprocessor and reconfigurable logic device and has high speed communications channels for inter-node communication. The design of the node provided high-speed serial communications channels allowing the implementation of various network topographies. The node also provided a PCI master interface to provide an external interface and communicate with local nodes on the bus. A high speed RlSC processor provided communication and system control functions and the reconfigurable logic device provided communication interfaces and data processing functions. The node was designed and implemented as a PCI card that interfaced a standard PCI bus. VHDL designs for logic devices that provided system support were developed, VHDL designs for the reconfigurable logic FPGA and software including drivers and system software were written for the node. The 64-bit version Linux operating system was then ported to the processor providing a UNIX environment for the system. The node functioned as specified and parallel and hardware accelerated processing was demonstrated. The hardware acceleration was shown to provide substantial performance benefits for the system

Accelerating Gauss-Newton filters on FPGA's

Includes bibliographical references (leaves 123-128).Radar tracking filters are generally computationally expensive, involving the manipulation of large matrices and deeply nested loops. In addition, they must generally work in real-time to be of any use. The now-common Kalman Filter was developed in the 1960's specifically for the purposes of lowering its computational burden, so that it could be implemented using the limited computational resources of the time. However, with the exponential increases in computing power since then, it is now possible to reconsider more heavy-weight, robust algorithms such as the original nonrecursive Gauss-Newton filter on which the Kalman filter is based. This dissertation investigates the acceleration of such a filter using FPGA technology, making use of custom, reduced-precision number formats

Towards effective modeling and programming multi-core tiled reconfigurable architectures

For a generic flexible efficient array antenna receiver platform a hierarchical reconfigurable tiled architecture has been proposed. The architecture provides a flexible reconfigurable solution, but partitioning, mapping, modeling and programming such systems remains an issue. We will advocate a model-based design approach and propose a single semantic (programming) model for representing the specification, design and implementation. This approach tackles these problems at a higher conceptual level, thereby exploiting the inherent composability and parallelism available in the formalism. A case study illustrates the use of the semantic model with examples from analogue/digital co-design and hardware/software co-design

Parallel implementation of pulse compression method on a multi-core digital signal processor

Pulse compression algorithm is widely used in radar applications. It requires a huge processing power in order to be executed in real time. Therefore, its processing must be distributed along multiple processing units. The present paper proposes a real time platform based on the multi-core digital signal processor (DSP) C6678 from Texas Instruments (TI). The objective of this paper is the optimization of the parallel implementation of pulse compression algorithm over the eight cores of the C6678 DSP. Two parallelization approaches were implemented. The first approach is based on the open multi processing (OpenMP) programming interface, which is a software interface that helps to execute different sections of a program on a multi core processor. The second approach is an optimized method that we have proposed in order to distribute the processing and to synchronize the eight cores of the C6678 DSP. The proposed method gives the best performance. Indeed, a parallel efficiency of 94% was obtained when the eight cores were activated