High-frequency (HF) radar plays a crucial role in the detection of far-range, stealth, and high-speed targets. Nevertheless, the echo signal of such targets typically exhibits a low signal-to-noise ratio (SNR) and significant amplitude fluctuations because their radar cross-section (RCS) accounting for the HF band is in the resonance region. While enhancing detection performance often requires long-time integration, existing algorithms inadequately consider the impact of amplitude fluctuation. In response to this challenge, this article introduces an improved approach based on coherent and non-coherent integration. Initially, coherent integration, employing the generalized Radon Fourier transform (GRFT), is utilized to derive a candidate detection set of targets’ range–time trajectories. This involves a joint solution for range migration (RM) and Doppler frequency migration (DFM) through a multi-parameter motion model search. Subsequently, the removal of low SNR pulses, followed by non-coherent integration, is implemented to mitigate amplitude fluctuation, referred to as Amplitude Fluctuation Suppression (AFS), and refine the detection outcomes. Both simulation and experiment results are provided to prove the effectiveness of the proposed AFS-GRFT algorithm.

Noncontact flow measurement methods have been popular among hydrographers for their convenient and safe operation in recent years. Ultrahigh frequency (UHF) radar is an essential flow measurement instrument that is normally deployed on the river bank to monitor flow velocity and discharge. However, when the river flow is too high, some frequency points of the Doppler spectrum are aliased. The frequency point in the aliased first-order peak region may contain more than one current signal, which cannot be distinguished by the previous radial current extraction methods. The consequent poor radial current decreases the estimation performance of cross-sectional surface velocity and river discharge. This letter first interprets the mechanism of the aliasing phenomenon according to the relationship between Bragg frequency and Doppler shift. Then, a radial current extraction method based on the classification of Doppler frequency points is proposed to solve the aliasing problem. Experimental results demonstrate that the proposed method outperforms the other two radial current extraction methods in calculating discharge with a reduction in a root-mean-square error (RMSE) of 364 and $574 \mathrm {m^{3}/s}$ , respectively.

Compact high-frequency (HF) surface wave radar can be used for remote sensing of sea surface dynamic parameters such as winds, waves and currents, as well as hard targets such as ships and low-altitude aircrafts. Due to its small antenna aperture, compact HF radar usually has a large error in direction of arrival (DOA) estimation, which significantly reduces its accuracy of target tracking. For a high-speed target, the DOA estimation error is greater due to range migration (RM) and Doppler frequency migration (DFM) as well as rapid change in the DOA of target echo. A high-speed target tracking method for compact HF radar is proposed in this paper, which utilizes the zero-mean property of the DOA error. First, the generalized Radon Fourier transform (GRFT) is used to estimate the target's motion parameters, and the multiple signal classification (MUSIC) algorithm is used to estimate the target's DOA. The original target track is obtained by combining the range and DOA estimates. Next, multiple positions on the original track are selected as the base points, and for each base point, a predicted track can be calculated based on the target motion parameter estimates, thus multiple predicted tracks are obtained. Then, these predicted tracks are screened according to their headings. The remaining predicted tracks after screening are fused to obtain the final track. Numerical simulations and field experiments demonstrate that this method reduces the impact of DOA error on tracking accuracy and expands the application of compact HF radar for high-speed target tracking.

With the rapid advancement of 5G communication technology, electrical systems place increasingly stringent demands on filters in terms of miniaturization, low cost, and high performance. Traditional filter circuit topologies and fabrication technologies are often unable to meet these requirements. Therefore, this manuscript proposes an improved filter circuit topology and implements it using thin-film integrated passive device (IPD) technology. First, based on the traditional filter circuit topology, the transmission zero point is introduced and a symmetrical design is adopted, which significantly improves the filter’s stopband rejection and design flexibility. Next, based on the improved circuit topology and the proposed IPD process, a compact three-dimensional (3D) chip filter is developed through spatial layout optimization. Finally, the effectiveness of the improved circuit topology is validated by fabricating two bandpass chip filter on gallium arsenide (GaAs) substrates for 5G communication applications. The fabricated filter chip exhibits an insertion loss of 2.09 dB in the passband, a stopband rejection greater than 40 dB, a shape factor of 1.64, and a compact size of only 1.0 mm×0.8 mm (0.012 λ₀× 0.010 λ₀).