The ability to identify human movements can serve as an important tool in many different applications such as surveillance, military combat situations, search and rescue operations and patient monitoring in hospitals. This information can provide soldiers, security personnel and search and rescue workers with critical knowledge that can be used to potentially save lives and/or avoid dangerous situations. Most research involving human activity recognition employs the short‐time Fourier transform (STFT) as a method of analysing human micro‐Doppler signatures. However, the STFT has time–frequency resolution limitations and Fourier transform‐based methods are not well‐suited for use with non‐stationary and non‐linear signals. The authors approach uses the empirical mode decomposition to produce a unique feature vector from the human micro‐Doppler signals following which a support vector machine is used to classify human motions. This study presents simulations of simple human motions, which are subsequently validated using experimental data obtained from both an S‐band radar and a W‐band millimetre wave (mm‐wave) radar. Very good classification accuracies are obtained at distances of up to 90 m between the human and the radar.

A novel coherent ultra-wideband radar system operating in the 1- to 2-GHz frequency range has been developed recently at the University of Nebraska. The radar system transmits white Gaussian noise. Detection and localization of buried objects is accomplished by correlating the reflected waveform with a time-delayed replica of the transmitted waveform. Broadband dual-polarized log-periodic antennas are used for transmission and reception. A unique signal-processing scheme is used to inject coherence into the system by frequency translation of the ultrawideband signal by a coherent 160-MHz phase-locked source prior to performing heterodyne correlation. The system coherence allows the extraction of a target’s polarimetric amplitude and phase characteristics. This paper describes the unique design features of the radar system, develops the theoretical foundations of noise polarimetry, provides experimental evidence of the polarimetric and resolution capabilities of the system, and demonstrates results obtained in subsurface probing applications. © 1998 Society of Photo-Optical Instrumentation Engineers.

This study presents the results of the authors’ experimental investigation into the radar micro‐Doppler signatures (MDS) of various human activities both in free‐space and through‐wall environments. The collection of MDS signatures was divided into three categories: stationary, forward‐moving, and multi‐target. Each category of MDS signatures encompassed a variety of movements associated with it, adding up to a total of 18 human movements. Using a 6.5‐GHz C‐band coherent radar, the MDS of six human subjects were gathered in free‐space and through‐wall environments. The MDS for these cases were analysed in detail and the general properties of the signatures were related to their associated phenomenological characteristics. Based upon the MDS, features for designing detectors and classifiers of human targets performing such movements are recommended. In the case of multiple human targets in the radar field of view, it was found that it is possible to distinguish these targets from the MDS under certain circumstances, but not under others.

We investigate three emerging topics essential for the development of cognitive radar (CR) for spectrum sharing: the response time (RT) of the CR, the autonomous regulation of the perception-action cycle (PAC), and the regulation of cognition. The RT measures the latency of all algorithms/hardware and is examined with respect to enabling capabilities of software-defined systems for rapid flexibility and responsiveness. The autonomous regulation of the PAC determines “how fast the CR can interact with the environment” as well as “how fast the CR should interact with the environment.” The regulation of the PAC is explored with respect to pulse-to-pulse waveform agility to coexist successfully with dynamic radio frequency emitters in the ambient electromagnetic environment (EME) and the consequence of modifying the waveform within the coherent processing interval. Finally, the regulation of cognition determines how to select a particular CR technique appropriately for a given dynamic environment. This selection requires a high level, or metadecision process to identify the appropriate CR technique as the EME changes over time and we therefore concentrate discussion on the newly emerging topic for radar called metacognitive radar. The exploration of these three topics include a review of past and current research with discussion of possible future research.

The University of Nebraska has developed a multiwavelength airborne polarimetric lidar (MAPL) system to support its Airborne Remote Sensing Program for vegetation remote sensing. The MAPL design and instrumentation are described in detail. Characteristics of the MAPL system include lidar waveform capture and polarimetric measurement capabilities, which provide enhanced opportunities for vegetation remote sensing compared with current sensors. Field tests were conducted to calibrate the range measurement. Polarimetric calibration of the system is also discussed. Backscattered polarimetric returns, as well as the cross-polarization ratios, were obtained from a small forested area to validate the system’s ability for vegetation canopy detection. The system has been packaged to fly abroad a Piper Saratoga aircraft for airborne vegetation remote sensing applications.