Multiple Compressive Projection Measurement for Stepped Frequency Radar

In modern communication and measurement sys- tems, signal detection and estimation play a major role. Actually, the above two terms can be considered as one issue, e.g. pure detection by densely listing all possible diversites. The penalty is however the system complexity. Up to now, a lot of work have been invested, especially the recent compressed sensing (CS) technique [1], which is a subtle mathmatic application in practice and leads to a great sucess in signal detection both for communication and measurement, e.g. radar technique. In spite of this radical progress there are still a lot of open problems. One of them is the "noise" including background noise and non- ideal signal modelling, which is not just a problem for CS but a general difficulty for signal processing. Although there are many sophisticated recovery algorithms developed to cope with noise, the performance will be usually impacted by inaccurate noise estimation or modelling error. In this paper, we will analyti- cally describe the multiple compressive projection measurement (mCPM1 or MCPM) introduced in [2]. Both theoretical analysis and numerical evaluations show that mCPM is a promising measurement system.