In the field of maritime surveillance, the global navigation satellite system (GNSS)-based passive radar has proven its potential for moving target detection (MTD), localization, and velocity estimation. The next stage is to investigate the possibility of obtaining the radar image of the moving ship for target recognition. However, the limited signal power budget of GNSS prevents the conventional inverse synthetic aperture radar technique that is based on target rotational motion and short observation time for GNSS-based passive radar imaging moving target. In this article, a two-stage imaging processing method relying on the target translational motion over a long observation time is proposed. The first stage confirms the presence of the target by a long-time MTD processing technique. In the second stage, based on the analysis of the Doppler history of the target signal in the slow-time domain, short-time Fourier transform and modified random sample consensus are combined to robustly estimate target velocity with reduced computation complexity. To obtain the focused bistatic image, azimuth compression is conducted by using the estimated target velocity. Finally, an image fusion operation is implemented to combine the bistatic images achievable from multiple satellites so that a multistatic image with high quality can be created. The effectiveness of the proposed method is confirmed by the real experimental results of three cargo ships illuminated by several satellites.

In the post-cloud computing era, edge computing as a distributed computing paradigm, integrating the core capabilities of computing, storage, network, and application, provides EIS (edge intelligence service), such as real-time business, data optimization, intelligent application, security, and privacy protection. The EIS has become the core value driver to promote the IoE (Internet of Everything), to dig deeply into data value and create a new ecology of application scenarios. With the emergence of new business processes, EIS orchestration has also become a hot topic in academic research. A design methodology based on a complete “describe-synthesize-verify-evaluate” process was established to explore executable design specifications for EIS by means of model validation and running instances. As proof of concept, a CPN (colored Petri net) prototype was simulated and its operational processes were discovered by process mining from event data available in EIS for behavior verification. The instances running on WISE-PaaS demonstrate the feasibility of the research methodology, which aims to optimize EIS through service orchestration.