Dr. Ling's research interests include computational electromagnetics, antenna and propagation, and radar sensors and radar signal processing.
Wind power is becoming an important source of alternative energy as the world moves to drastically reduce greenhouse gas emissions in the next decade. While the number of wind farms is growing rapidly around the world, the detrimental effect of wind farms on existing radar systems is raising serious concerns. Wind farms create strong Doppler clutter and deep electromagnetic shadow that can lead to false alarms and missed detection of real targets of interest like aircraft and storms. A number of studies have been commissioned both in the US and abroad to assess the effect of wind farms on air defense, air traffic control and weather radars. Despite these efforts, the interfering effects of wind farms on radar are not well understood.
The objective of this research is to gain an in-depth understanding of electromagnetic scattering from wind farms. Our approach entails three steps: (i) develop and apply innovative simulation techniques to predict and analyze dynamic radar signatures of wind farm scattering, (ii) develop and apply measurement techniques to acquire scaled model and in-situ measurement data from wind farms to corroborate the simulation, and (iii) exploit the resulting knowledge by investigating radar interference mitigation techniques and wind turbine monitoring applications. The problem is challenging from both the simulation and measurement perspectives because of the unique shape of the structure, the time-varying nature of the scattering phenomenology and the very large physical as well as electrical size of the problem.
Standoff detection of explosives and related threats is a current challenge for the United States government in connection with anti-terrorism operations, urban warfare and homeland defense. A potentially useful and technically feasible area of development is radio frequency (RF) sensors to detect and monitor human activities associated with bomb making and bomb delivery from a standoff distance. RF sensors provide unsurpassed range, 24-7 operation and good penetration through building walls. Human body and limb movements also result in unique “microDoppler” features that can be detected easily. There are a number of ongoing through-wall radar sensing programs funded by the US government.
Antennas are an indispensable component in any RF communication or sensing system. The design of antennas is a cut-and-try process that can be greatly enhanced by the use of a computational electromagnetic solver coupled with an effective optimization algorithm. In our research, we are exploring various design methodologies such as genetic algorithms, particle swarm optimization, artificial neural networks, and vector fitting to achieve antenna designs with optimal performance. The topics of our investigation include: (i) electrically small antennas, (ii) ultra-wideband antennas, (iii) reconfigurable supergain arrays, and (iv) antenna circuit modeling.
During the last two decades, our research group has actively contributed to the development and validation of numerical and asymptotic methods for characterizing radar scattering from complex targets. In 1985, we helped pioneer the shooting and bouncing ray (SBR) technique for predicting radar returns from realistic aerospace vehicles. Through our research efforts, the concept of SBR was realized for predicting radar signatures of complex air and ground targets described by three-dimensional computer models. In the 1990s, our research group devised a number of fast algorithms that led to order-of-magnitude improvements in the speed and accuracy of the SBR technique. Our research in SBR theory has directly contributed to the development of the industry-standard signature prediction code Xpatch.