Except for the slight difference of micromotion parameters, some decoys and warheads have
the same geometry and micromotion form. As a result, recognition of similar space cone …

An effective method for identifying inertia characteristics of cone-shaped space target based
on deep learning is proposed. The inertia ratio is determined by the time-varying scattering …

High-resolution range profile (HRRP) sequences have great potential for space target
classification because they can provide both scattering information and micromotion …

Energy saving becomes a central issue in the design of wireless sensor networks routing
algorithms. The objective of this study is to maximize the survival time of wireless sensor …

Micro-Doppler is regarded as a unique signature of a target with micro-motions. The
sophisticated recognition of the cone-shaped targets can be realized through the micro …

Precession is a typical micromotion of a ballistic missile warhead in the middle of the
trajectory. The modulation of the narrow-band radar echo by the precession warhead is …

Wireless sensor networks exploit clustering and routing techniques to improve energy
efficiency, but these methods are generally considered as a non-deterministic polynomial …

Micro-Doppler shift induced by precession is crucial for ballistic target recognition. However,
traditional single radar has the limitation of single viewing angle, while radar network (RNW) …

Space target classification based on micro-motion characteristics has become a subject of
great interest in the field of radar, particularly when using deep learning techniques …

In this article, we propose a new signal-decomposition algorithm composed of three steps:
principal components analysis to yield high-resolution range profiles with improved signal-to …