## 1 Introduction  
Near-field measurements have been widely used in electromagnetic compatibility (EMC) applications, especially in the electromagnetic interference (EMI) detection of large-scale integrated circuits (ICs) and the EMI source location of high-speed printed circuit boards (PCBs) [1], etc. Meanwhile, the transmission characteristics of interconnects are receiving a lot of attention in high-speed and fast-switching PCBs. Interconnect-induced emissions and signal quality degradations become increasingly difficult to be ignored as the transmission and switching speeds increase. It is convenient and efficient to detect the transmission characteristics from near-field emissions in order to diagnose abnormal functionalities and achieve a good signal quality along the traces. For near-field emission characteristics extraction, the commonly accepted method is interference sources identification [2; 3; 4; 5]. However, electromagnetic emission is an inherent property of the product, which is determined by the interference sources and peripheral circuits [2]. For example, the ring generated by the mismatch can cause the spectrum to rise at a particular frequency [6]. In it, a method for extracting the mismatch characteristics from a conducted emission spectrum was proposed using particle swarm optimization (PSO). A method for extracting the noise source impedance of switched-mode power supplies (SMPS) during operational conditions was presented [7]. The impedance can be used to model the equivalent circuit of the conducted emission with the interference sources. The authors of [8] extracted the transmission characteristics of peripheral circuits from digital circuit-induced emissions based on the autocorrelation function, but the transmission characteristics are not physical. The methods noted above are all used for the conducted analysis, and we mainly focus on frequencies lower than 1 GHz. For other noncontact measurements, there are mainly two approaches that have been reported. The first one measures the surface electric and magnetic field distributions of the circuits using near-field probes. This technique can be used for a performance and failure analysis in microwave circuits [9; 10; 11]. One measures the S-parameters of the traces using capacitive or inductive probes, in which the calculation of the propagating waves is achieved by using two probes separated by a certain distance or a single probe moved to two locations [12; 13; 14]. In addition, a probe was used to measure the current and voltage on a trace; an algorithm was also used based on the transfer functions to quantify the capacitive and inductive couplings between the probe and the trace during the test [15; 16; 17]. Meanwhile, most studies on interconnects have concentrated on the characteristics calculation. The authors of [18; 19; 20] proposed methods that can contribute to fast analysis, which are based on the physics-based via and trace models. The method in [21] combined a systematic analysis with an evaluation of energy efficiency to find improved off-chip interconnect design solutions, while the authors of [22] used artificial neural networks (ANNs) as a surrogate model to optimize the energy-efficient on-chip interconnect. In this study, we present a new measurement and analysis method for extracting the transmission characteristics of interconnects from near-field emissions in PCBs. By adopting using a wideband microstrip line electric probe, near-field emissions are captured. By applying the transfer function between the printed traces being tested and the probe and the reconstructed input signal waveforms, the transmission characteristics can be extracted from the emission. The transfer function is modeled using equivalent circuits, which is validated by full wave simulation and an experiment. The algorithm is programmed based on the autocorrelation function, adaptive wind-driven optimization (AWDO), and Fast Fourier transformation (FFT).