Jie Wang

In recent years, joint wireless communication and Synthetic Aperture Radar (SAR) imaging has received extensive attention. The realization of this concept remains a significant challenge. For communication and SAR, they have conflicting requirements on waveforms. The state-of-the-art solutions are based on the Orthogonal Frequency Division Multiplexing (OFDM) techniques. However, OFDM waveforms are sensitive to the Doppler frequency. Even worse, their unavoidable Cyclic Prefix (CP) would introduce false peaks into SAR images. To be insensitive to frequency bias and free of CPs, Filter Bank Multicarrier (FBMC) waveforms with stepped frequency chirp and Offset Quadrature Amplitude Modulations (OQAM) are proposed in this paper. Particularly, stepped frequency chirps, which have been optimally weighted for SAR imaging, are interleaved into FBMC subcarriers as pilots. Meanwhile, the channel changes can be obtained from these pilots for communication equalization. Moreover, concerning the intrinsic interference of imaginary parts between pilots and OQAM symbols, compensation algorithms are introduced. With the proposed waveform schemes, the identical frequency band can be utilized for data transmission while performing high-resolution SAR imaging. Theoretical analysis and simulation results demonstrate that the proposed waveform scheme is feasible.

In this paper, a new-brand feature-based detector via an improved concave hull classifier (FB-ICHC) is proposed to detect marine small targets. The dimension of feature space is suggested to be three, making a compromise between high detection accuracy and low computational cost. The main contributions are in the following two aspects. On the one hand, three features are well-designed from time series and Doppler spectrum, called relative phase zero ratio (RPZR), relative variation coefficient (RCV), and whitened peak height ratio (WPHR). RPZR can measure the pseudo-period properties in phase time series, insensitive to SCRs. In the Doppler spectrum, RCV reflects fluctuation variation in high SCR cases and WPHR describes the intensity property after clutter suppression in low SCR cases. On the other hand, in 3D feature space, an improved concave hull classifier is developed to further shrink the decision region, where a fast two-stage parameter search is designed for low computational cost and accurate control of false alarm rate. Finally, experimental results using open-recognized datasets show that the proposed FB-ICHC detector can improve detection performance by over 20% and reduce runtime by over 49%, compared with existing feature-based detectors with three features.

Remote sensing scene knowledge graphs symbolically describe the concepts of scenes and reveal their interrelations, highlighting robust knowledge modelling and inference capabilities in zero-shot remote sensing scene classification tasks. However, current graphs rely heavily on expert manual interpretation, making them susceptible to human biases and difficult to expand. They also lack quantitative description of the degree of spatial relationship associations and fail to adequately represent semantic information. Additionally, they often overlook discriminative local landscapes, which is crucial for accurate scene classification. To address these limitations, this article proposes the “Zero-Shot Remote Sensing Scene Classification via Automatic Knowledge Graph and Dual-Branch Semantic Correlation Supervision (AKG-DBSS).” This method starts with the scenes and automates the construction of a knowledge graph, “Scene-Landscape-Ground objects” (ASLG-KG), by analyzing the composition and spatial distribution of ground objects in local regions. On this basis, the dual-branch semantic correlation supervised zero-shot remote sensing scene classification network (DBSS) supervises the mapping of semantic features to the visual space via both global and local branches, ensuring the visual space reflects the correlation structure of the semantic space. Extensive experiments on the UCM, AID, and NWPU datasets demonstrate that AKG-DBSS achieves class average accuracy and overall accuracy of up to 98%, and 59.56%, respectively for the classification of unseen class scenes, with standard deviations below 6.91%, significantly outperforming four other advanced comparative methods. Furthermore, additional experiments prove that ASLG-KG and DBSS are feasible, necessary, and effective, with an accuracy improvement in overall accuracy of over 8.98%.

Special attention has been devoted to joint wireless communication and radar sensing concepts over the past decades. Considerable confusion arose, however, with regard to waveform designs. In this paper, various joint wireless communication and radar sensing waveform schemes are reviewed and classified into two categories. Disadvantages and limitations of each category are clarified theoretically. It is shown that waveforms designed merely in conventional time and frequency domains cannot fulfill the conflict requirements posed by radar and wireless communication. As a solution to this fundamental challenge, the multidimensional waveform concepts, along with a generalized correlation model, are proposed for joint wireless communication and radar sensing. To showcase our current research advances in this emerging area, several concrete waveforms designed in multiple dimensions are introduced. Theoretical analysis is validated by simulations and outfield demonstration experiments. It is shown that the suggested waveforms can simultaneously achieve superior detection and communication performances with shared spectrum resources.

Filters play an invaluable role in most detection and communication systems, blocking unwanted, harmonic or mirrored waves. In this paper, two $3^{\mathrm {rd}}$ -order quasi-elliptical waveguide bandpass filters working at 400 GHz are developed based on TE ₁₀₂ -mode oversized resonators. Transmission zeros are generated through the physical cross-couplings and the mixed modal bypass couplings. $H$ -plane off-axis coupling structures without any fragile irises are adopted to strengthen robustness and simplify manufacturing at such high terahertz frequencies. Effects of processing uncertainties on filters performance are discussed in detail to display error sensitivity. Two computer numerical control (CNC) machined filters exhibit a minimum insertion loss of about 1.5 dB in a 3 dB fractional bandwidth (FBW) with 12% centered at 390 GHz @ Filter-I, and 9% FBW with a center frequency of 394 GHz @ Filter-II, which are all mainly agreement with simulations. The performance is highlighted with the reported terahertz filters, which indicates that both architectural designs are still suited for the delicate CNC-milling restriction in such high WR-2.2 band.

Synthetic aperture radar (SAR) systems have extensively contributed to diverse scientific applications in the recent past decades. For the next generation of top-level SAR systems, the multimodal operation of wide swath imaging, sliding spotlight, and highly sensitive ground moving target indication (GMTI) is becoming increasingly crucial. Following this concept, in this article, a novel airborne multiple-input–multiple-output (MIMO) SAR system, along with the space–time coding (STC) waveform scheme and the phased array, is developed to realize the multimodal operation. In particular, the airborne MIMO SAR system consists of two transmitters and four receivers. The signals of the multiple modes, which overlap in the frequency domain, are interpulse modulated and transmitted by different subarrays concomitantly. The superposed echoes are separated by range-Doppler filtering. Based on the separated echoes, we can obtain eight equivalent transceiver channels and, as a result, enhance the signal-to-noise ratio (SNR) for airborne multimodal operation. In the future, the STC waveform scheme and flight experiments of this novel airborne MIMO SAR system will be further investigated to reduce the pulse repeat frequency (PRF) for spaceborne multimodal operation.