PBR Clutter Suppression Algorithm Based on Dilation Morphology of Non-Uniform Grid

Many new challenges are faced by the PBR (passive bi-static radar) employing non-cooperative radar illuminators. After the CFAR (constant false alarm) processor, the appearance of the amount of false alarm clutter points impacts the following tracing performance. To enhance the PBR tracing performance, we consider to reduce these clutter points before target tracing as soon as possible. In this paper, we propose a PBR clutter suppression algorithm based on dilation morphology of non-uniform grid. Firstly, we construct the non-uniform polar grid based on the acquisition geometry of PBR. Then, with the help of the grid platform, we separate the false alarm clutter points based on the dilation morphology. To efficiently operate the algorithm, we build up its parallel iteration scheme. To verify the performance of the proposed algorithm, we utilize both simulated data and field data to do the experiment. Experimental results show that the algorithm can effectively suppress most of the clutter points. Besides, we respectively combine the proposed suppression algorithm with two typical tracking algorithms to test the performance. Experimental results reveal that the compound tracing algorithm outperforms the traditional one. It can enhance the PBR tracing performance, reduce the occurrence probability of false tracks and meanwhile save time.

Intelligent Micro Energy Grid in 5G Era: Platforms, Business Cases, Testbeds, and Next Generation Applications

As fifth-generation mobile communication systems give rise to new smart grid technologies, such as distributed energy resources, advanced communication systems, the Internet of Things, and big data analytics, the development of novel platforms and business models that ensure reliability and profitability of microgrid operations become increasingly important. In this study, we introduce an open micro energy grid platform to operate the widely distributed microgrids in Korea. Subsequently, we present commercial microgrid business models supported by the open micro energy grid platform equipped with an artificial intelligence engine and provide test results from testbeds connected to the platform. In contrast to the existing microgrid business models in the market, we propose a universal architecture and business model of the future microgrid, comprising (i) an energy robot-management operation business model, (ii) electric vehicle-based demand response, (iii) blockchain technology for energy trading, and (iv) a service-oriented business model. Finally, we propose a new business model for an intelligent virtual power plant (VPP) operator along with the architecture of the VPP and its proof of concept (PoC). We expect the proposed business model to provide energy solution providers with guidelines to develop various VPP services.