February 29, 2016
Review of Radar Science, Technology, Applications, News, Publications, Industry, History, etc.
Wednesday, March 2, 2016
Revealed: Pentagon’s Plan to Defeat Russian and Chinese Radar With A.I.
February 29, 2016
Tuesday, April 22, 2014
Friday, April 4, 2014
Get ready for software-defined RADAR
With a big RF transmitter and enough fast computing power, you have the ability to do a lot of different things, as evidenced by a General Electric presentation on "software-defined radar" at the GPU conference this year.
At GTC 13 last year, GE gave a standing-room-only presentation about how it's using RDMA (Remote Direct Memory Access) to drive multi-GPU process performance to new heights. The firm was back this year to talk about new and innovative applications of GPU tech it has cooked up over the past year.
How it works: Simultaneous transmit/receive for a whole load of functions
In its session, Dustin Franklin, GE GPU Applications Engineer guru, gives us an update on how it has been proceeding with RDMA and how it allows the electric company to build large scale, multi-node, products.
Monday, April 15, 2013
Cognitive Radar Network: Cooperative Adaptive Beamsteering for Integrated Search-and-Track Application
Romero, R.A.; Goodman, N.A., "Cognitive Radar Network: Cooperative Adaptive Beamsteering for Integrated Search-and-Track Application," Aerospace and Electronic Systems, IEEE Transactions on , vol.49, no.2, pp.915,931, APRIL 2013
doi: 10.1109/TAES.2013.6494389
Abstract: Cognitive radar (CR) is a paradigm shift from a traditional radar system in that previous knowledge and current measurements obtained from the radar channel are used to form a probabilistic understanding of its environment. Moreover, CR incorporates this probabilistic knowledge into its task priorities to form illumination and probing strategies, thereby rendering it a closed-loop system. Depending on the hardware's capabilities and limitations, there are various degrees of freedom that a CR may utilize. Here we concentrate on spatial illumination as a resource, where adaptive beamsteering is used for search-and-track functions. We propose a multiplatform cognitive radar network (CRN) for integrated search-and-track application. Specifically, two radars cooperate in forming a dynamic spatial illumination strategy, where beamsteering is matched to the channel uncertainty to perform the search function. Once a target is detected and a track is initiated, track information is integrated into the beamsteering strategy as part of CR's task prioritization.