On sequential Monte Carlo sampling methods for Bayesian filtering
Statistics and Computing
Fast Prototyping of Datapath-Intensive Architectures
IEEE Design & Test
Efficient hardware controller synthesis for synchronous dataflow graph in system level design
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Code Generation of Data Dominated DSP Applications for FPGA Targets
RSP '98 Proceedings of the Ninth IEEE International Workshop on Rapid System Prototyping
Adaptive joint detection and decoding in flat-fading channels via mixture Kalman filtering
IEEE Transactions on Information Theory
Flexible Controller Design and Its Application for Concurrent Execution of Buffer Centric Dataflows
Journal of VLSI Signal Processing Systems
Study of Algorithmic and Architectural Characteristics of Gaussian Particle Filters
Journal of Signal Processing Systems
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We present an efficient physical realization method of particle filters for real-time tracking applications. The methodology is based on block-level pipelining where data transfer between processing blocks is effectively controlled by autonomous distributed controllers. Block-level pipelining maintains inherent operational concurrency within the algorithm for high-throughput execution. The proposed use of controllers, via parameters reconfiguration, greatly simplifies the overall controller structure, and alleviates potential speed bottlenecks that may arise due to complexity of the controller. A Gaussian particle filter for bearings-only tracking problem is realized based on the presented methodology. For demonstration, individual coarse grain processing blocks comprising particle filters are synthesized using commercial FPGA. From the execution characteristics obtained fromthe implementation, the overall controller structure is derived according to the methodology and its temporal correctness verified using Verilog and SystemC.