This paper presents a multiple-resonance technique that sought to achieve a wide bandwidth for printed wide-slot antennas with fork-shaped stubs. By properly appending an extra fork-shaped stub onto the main fork-shaped stub, the impedance bandwidth was able to be clearly broadened. To validate this technique, two designs where the extra stubs were added at different positions of the main stub were constructed. The measured impedance bandwidths of the proposed antennas reached 148.6% (0.9–6.1 GHz) for S₁₁ < −10 dB, indicating a 17.9% wider bandwidth than that of the normal antenna (0.9–4.3 GHz). Moreover, a stable radiation pattern was observed within the operating frequency range. The proposed antennas were confirmed to be much-improved candidates for applications in various wireless communication systems.

Navigation satellite signals have the advantages of all-day, all-weather, and global coverage, and the use of navigation signals for the detection of moving targets has significant application prospects. However, the GNSS signal is very weak, and the signal power is greatly attenuated after being scattered by the target. In order to detect the echo signal, a long integration time is required. However, the movement of the target will cause the echo signal to produce unpredictable range migration and a Doppler frequency shift, which will weaken the cumulative effect of long-term integration. This paper proposes a weak signal processing method with amplitude and phase self-correction for moving target detection in the GNSS-S radar. First, the phase consistency of the echoes of a single GNSS satellite is realized by the block expansion compression and phase differential correction method to improve the coherent accumulation gain; then, multi-star joint accumulation is carried out after the signal amplitudes of multiple satellites are corrected by the improved keystone method, so as to obtain a stable echo signal track. This method can effectively improve the integral gain of the scattering signal of the moving target and realize target detection. The simulation results and field tests show that this method can effectively improve the SNR of the GNSS-S signal and can realize the detection of small moving targets such as cars with GNSS-S radar.

Detecting tiny targets, a fundamental satellite observation task, always suffers from information loss, additional computation costs, and imbalance samples in full-scene imagery. However, generic methods rely on complex deep neural networks to traverse every region of the image, irrespective of the non-uniform target distribution, severely hindering the detecting accuracy and leading to a heavy computation burden. This paper proposes a feature focusing super-resolution small target detection network (FFSSTD-Net), alleviating the above three problems. First, the proposed convolution focus detection module (CFD) uses a lightweight full-convolutional network query mechanism to adaptively search the regions with targets, eliminating unnecessary computation costs and noise from the background. Then, the proposed feature super-resolution (FSR) module guides the backbone network enhancing the representation of small target objects in high-dimensional features through an auxiliary branch to achieve a balanced optimization, alleviating the information loss caused by sub-sampling operations. Experimental results demonstrate that the FFSSTD-Net outperforms state-of-the-art generic methods, improving mAP and Fps by at least 3.14% and 10%, respectively. Meanwhile, ablation experiments indicate that the CFD and FSR modules enhance detection accuracy while accelerating full-scene image processing.

This work presents a novel image-based vital sign detection strategy for trapped persons based on the optimized 2-D UWB radar deployment. The main novelty is that the slow-time images based on 2-D radar deployment can be created to continuously screen the trapped persons with periodic micro-motions in a specific area. According to the optimized deployment, multiple UWB life-detection mono-static radars are distributed and work in a time-division-multiplexing mode. These radars are sequentially controlled and activated to capture information from all possible wave incidents and scattering angles. The 2-D radar deployment is designed and optimized using the MIMO array topology technique. The vital sign is modeled as the slow-time image, and multiple images might contain the periodic weak responses from the trapped persons. Proof-of-principle experiments were also carried out based on an optimized 2-D UWB radar deployment. All observation points in this deployment are sequentially selected to complete the transmission and reception of the UWB mono-static radar. Finally, the experimental results validate the effectiveness of the proposed image-based vital sign strategy on the azimuth locations of the trapped persons.

Global navigation satellite system (GNSS) array antenna receivers are widely used to suppress wideband interference in navigation countermeasures. However, existing array antenna receivers all adopt a digital array structure and digital beamforming technique, and they have limited analog-front-end (AFE) dynamic range. In strong interference scenarios, AFE saturation will occur, which limits the maximum interference suppression ability of the array receiver. Aiming at this issue, this paper proposes a robust wideband interference suppression method for GNSS array antenna receivers based on a hybrid beamforming technique. Firstly, a novel, fully connected hybrid array receiver structure is proposed. Secondly, the corresponding hybrid beamforming method is proposed at the same time, and it realizes the complete elimination of the strong wideband interference by joint suppression in the analog domain and digital domain. After mathematical simulations, it is verified that, compared to the digital beamforming-based anti-jamming technique, the proposed method can effectively suppress strong wideband interference, and the maximum interference suppression ability is improved by 36 dB.

In order to reduce the complexity of the receiving system for wideband signals, a novel space-borne high-resolution synthetic aperture radar (SAR) system with the non-uniform hybrid sampling technology is proposed in this paper. The non-uniform hybrid sampling technology is firstly applied in the SAR imaging system for the detection of space targets. The non-uniform hybrid sampling technology is able to optimize the transmitted and receiving timing of SAR signals, reducing the requirement of the sampling rate of the analog-to-digital converter (ADC) for the reception of the wideband echoes from space targets. Meanwhile, according to the oversampling requirement of SAR imaging in the azimuth direction, a theoretical model of non-uniform hybrid sampling parameters and relative velocity between the SAR system and the space targets is established. A series of simulation experiments with different targets and different non-uniform hybrid parameters are performed, and an X-band SAR imaging experimental system is constructed to verify the effectiveness of the proposed non-uniform hybrid sampling technology. The experimental results show that the imaging resolution is better than 8 cm. When the non-uniform hybrid sampling interval is 15 us, the imaging quality is consistent with imaging results of the Nyquist real-time sampling, and it is easier to implement in the high-resolution imaging for space targets.