This paper investigates the impact of incident beam inhomogeneity on the quality of THz imaging based on the compressed sensing (CS) method. Image sampling and reconstructions under point and Gaussian beams with various geometric parameters are compared with the standard one. The simulation results show that the geometric parameters of beams strongly affect the peak signal-to-noise ratio (PSNR) of the reconstructed images. Especially for the Gaussian one, expanding the beam size at the position of the mask (BZPM) dramatically increases the PSNR. To achieve high sensitivity and resolution, new measurement matrices correlating to the incident beam distribution are proposed and the simulation results are demonstrated. Experiments under VDI THz source reveal that by using the new matrices, the PSNR of CS-based imaging at 100 GHz is evidently improved from 6 dB to 13 dB, informing the new measurement matrices are highly efficient and accurate in removing the beam effect on CS-based THz imaging. Our results may provide a new way for the high-quality CS-based THz imaging for target recognition.

The resistive microbolometer fabricated by using CMOS technology can be monolithically integrated with the readout circuit but usually performs poorly in responsivity and detectivity. In this paper, the salicide poly-Si microbolometer with Al grating structure is demonstrated in the standard CMOS process. The simulation results show that not only are surface plasmon polaritons generated at the interface of the Al grating and SiO ₂ , Al grating also provides the infrared resonant cavity required for the absorber, which improves the responsivity of the microbolometer. According to the experimental results, the maximum detectivity of the microbolometer with the grating structure reaches up to 2.26 × 10 ⁹ cmHz ^1/2 /W at 10 μm, which means an increase by 27.8% compared to the one without the Al grating. Moreover, the average detectivity of the microbolometer is also improved when the wavelength ranges from 7 μm to 13 μm. It is effortless to implement the proposed high-performance microbolometer in a unit structure based on CMOS technology, which is favorable to high-density array integration.

With the development of automated driving applications, the micro-Doppler effect induced by the rolling wheels of the vehicles normally disturbs the target detection and the effect is difficult to be eliminated at close range. In this paper, illustrating the micro-Doppler motion of the rolling wheels, the asymmetric Doppler spectrum caused by the micro-Doppler interference is innovatively introduced. A random-finite-set (RFS)-based measurement model is applied to analyze the asymmetry. To eliminate the asymmetric phenomenon, a temporal smoothing method based on the cadence velocity diagram (CVD) is proposed. Simulations based on the RFS model and experiments prove the exhibition of the asymmetric micro-Doppler interference introduced by rolling wheels and the feasibility of the proposed elimination method. Moreover, compared with the state-of-the-art symmetry method, the detection probability improves from 80% to 93% when the false alarm rate is fixed at 10-6, informing that the proposed method is highly efficient and the false detection caused by micro-Doppler effect can be eliminated accurately. The results may provide a new way for high-quality wheeled vehicle detection.

A conventional target detection technique for FMCW millimeter‐wave radar applies a two‐dimensional (2D) cell‐averaging constant false alarm rate (CA‐CFAR) detector to all range‐doppler cells in order to suppress noise and clutter. However, this 2D CA‐CFAR method has significant drawbacks, particularly its high computational cost due to the large number of additions required, resulting in a time complexity of O(n ⁴ ). To decrease the computational complexity while ensuring the detection accuracy, a novelty CA‐CFAR technique based on the prefix sum algorithm with a complexity O(n ² ) is proposed in this article. Simulations verify the feasibility of the proposed method. Compared to both conventional and state‐of‐the‐art optimized CA‐CFAR techniques, the proposed method reduces the number of addition operations by 95%, lowers CFAR loss by approximately 0.5 dB, and improves the figure of merit (FOM) by about 20% at a fixed false alarm rate of 10 ⁻⁶ . This advanced technique offers significant computational efficiency for radar applications.

A conventional target detection technique for FMCW millimeter-wave radar applies a two-dimensional (2D) cell-averaging constant false alarm rate (CA-CFAR) detector to all range-Doppler cells in order to suppress noise and clutter. However, this 2D CA-CFAR method has significant drawbacks, particularly its high computational cost due to the large number of additions required, resulting in a time complexity of O(n^{4}). To decrease the computational complexity while ensuring the detection accuracy, a novelty CA-CFAR technique based on the prefix sum algorithm with the complexity O(n^{2}) is proposed in this article. Simulations prove the feasibility of the proposed method. Compared to both conventional and state-of-the-art optimized CA-CFAR techniques, the proposed method reduces the number of addition operations by 95%, lowers CFAR loss by approximately 0.5 dB, and improves the figure of merit (FoM) by about 20% at a fixed false alarm rate of 10^{-6}. This advanced technique offers significant computational efficiency for radar applications.