Yipeng Ding

Micro-Doppler Trajectory Estimation of Pedestrians Using a Continuous-Wave Radar

Radar backscattering from human objects is subject to micro-Doppler modulations because of their flexible body articulations and complicated movement patterns, which can help identify the interested targets and provide valuable information about their motion dynamics. In this paper, a novel theoretical method to extract target micro-Doppler trajectories from continuous-wave radar echo is proposed with a united application of a modified high-order ambiguity function and an adaptive denoising technology. Through this method, multiple components corresponding to different target scattering parts and their micro-Doppler trajectories can be accurately extracted and estimated even in a time-varying low signal-to-noise ratio environment. Finally, a series of simulations is conducted to illustrate the validity and performance of the proposed techniques.

Application of Linear Predictive Coding for Doppler Through-Wall Radar Target Tracking

In this letter, a target tracking approach, which combines short-time Fourier transform (STFT) and linear predictive coding (LPC), is proposed for a Doppler through-wall radar. The LPC is applied to extend the known echo data in each STFT sliding window, thus helping in improving the estimation accuracy of target instantaneous frequency. Compared with the traditional LPC process which determines the prediction data size empirically, the proposed approach takes advantage of the fitting error array as a control parameter to intelligently adjust the data size and reduce the prediction error. Moreover, the proposed approach can also enhance the radar processing efficiency by preventing the unqualified prediction data, which is of great importance for real-time detecting applications. Series of experimental measurements are presented as a preliminary assessment of the proposed approach.

Echo Interference Suppression Approach for Doppler Through-Wall Radar

Because of the particularity of through-wall radar (TWR) applications, TWR often operates in a complicated environment, which can lead to severe interferences in the received echo and thus hamper the accurate target detection. To solve the issue, in this paper, an echo interference suppression approach, which combines hardware and algorithm process, is proposed for Doppler TWR. Compared with the traditional methods, which mainly based on the fixed filter parameters, the proposed approach takes advantage of feedback structure and microcontroller to intelligently adjust the filter parameters according to the real-time interference variation and thus achieves not only more effective, but also more stable interference suppression performance even in a dynamic environment. Series of experimental measurements are presented to illustrate the performance of the proposed techniques.

Weak photoacoustic signal detection based on the differential duffing oscillator

In view of photoacoustic spectroscopy theory, the relationship between weak photoacoustic signal and gas concentration is described. The studies, on the principle of Duffing oscillator for identifying state transition as well as determining the threshold value, have proven the feasibility of applying the Duffing oscillator in weak signal detection. An improved differential Duffing oscillator is proposed to identify weak signals with any frequency and ameliorate the signal-to-noise ratio. The analytical methods and numerical experiments of the novel model are introduced in detail to confirm its superiority. Then the signal detection system of weak photoacoustic based on differential Duffing oscillator is constructed, it is the first time that the weak signal detection method with differential Duffing oscillator is applied triumphantly in photoacoustic spectroscopy gas monitoring technology.

Human Target Localization Using Hough Transform and Doppler Processing

In this letter, a localization algorithm, which combines Hough transform and Doppler processing, is proposed for Doppler radar human sensing applications. The Hough transform is first applied to extract the interested target components and real-time estimate their instantaneous frequencies (IFs). Then, based on the IF estimation result, the target movement trajectories are synthesized by Doppler processing. To improve the detection accuracy and robustness, a generalized linear model is proposed for Hough transform, which can achieve highly dimensional frequency fitting to compensate the nonlinear error, meanwhile maintaining a low level of computational complexity for real-time processing. Experimental results are presented to illustrate the performance of the proposed algorithm.

Self-calibration wavelength modulation spectroscopy for acetylene detection based on tunable diode laser absorption spectroscopy*

The expressions of the second harmonic (2f) signal are derived on the basis of absorption spectral and lock-in theories. A parametric study indicates that the phase shift between the intensity and wavelength modulation makes a great contribution to the 2f signal. A self-calibration wavelength modulation spectroscopy (WMS) method based on tunable diode laser absorption spectroscopy (TDLAS) is applied, combining the advantages of ambient pressure, temperature suppression, and phase-shift influences elimination. Species concentration is retrieved simultaneously from selected 2f signal pairs of measured and reference WMS-2f spectra. The absorption line of acetylene (C2H2) at 1530.36 nm near-infrared is selected to detect C2H2 concentrations in the range of 0–400 ppmv. System sensitivity, detection precision and limit are markedly improved, demonstrating that the self-calibration method has better detecting performance than the conventional WMS.