New tangible input techniques are transforming human-computer interaction. Point-contact devices such as joysticks or buttons are simple and scalable, but they capture limited spatial information. In contrast, surface-based contact interfaces such as touchpads provide richer spatial input but require larger instrumented surfaces. We present MagBall, a magnetic-ball sensor that captures fine-grained interactions, including displacement and force, through the rotation of a magnet-embedded ball over a 3D Hall-effect sensor array. Our design localizes diverse physical interactions to a single point-contact yet operates at multiple scales from millimeters to meters. Our machine learning models can infer the displacement and force with root-mean-squared errors of 0.15 mm and 0.67 N. Furthermore, our device supports interactions across diverse surfaces such as glass, metal and human skin, without additional instrumentation. We demonstrate applications in stylus pens, wearable trackballs and smart massage tools, which naturally aligns with the rolling mechanism of MagBall.

The 2-D space variance of echo signals is the key problem of image processing for bistatic synthetic aperture radar (BiSAR) under nonlinear platform trajectories. Although there are some existing studies that present solutions to deal with space variance under linear or low-order motion, this problem is more severe when the trajectories are more complicated and the imaging scene sizes are larger. To deal with this challenging problem, this article proposes a new imaging method based on a novel azimuth-regularized wavenumber mapping and a highly efficient spatially variable phase filter. The novel wavenumber mapping as the major novelty of the method can simultaneously realize range–azimuth decoupling and coarse focusing in the space domain for all the targets. What is more, the phase function of the echo signal in the wavenumber domain is analytically expressed as a binary polynomial by deriving the inverse mapping of the wavenumber with respect to range frequency and azimuth time. Then, the spatially variable filter is designed based on the analytical expression and realized by upgrading the parameters along the azimuth direction. The filtering process has low complexity and can be executed in parallel for every cross-azimuth cell. Moreover, an algorithm for constraining the residual phase error is presented to guarantee both the efficiency and the accuracy of the image processing. Verified by numerical simulations, the proposed imaging method achieves a superior focusing effect than the existing method that is designed for BiSAR with highly maneuvering platforms while having lower computational complexity.

This paper unrolls some preliminary results of a spaceborne-airborne bistatic SAR experiment, conducted in October, 2020 in Zhejiang, China, using GF-3 SAR satellite as the transmitter. Some important aspects of the experiment are firstly introduced, including bistatic acquisition geometry, receiving system, signal synchronization and theoretical spatial resolution. Then, the imaging processing flow is given, with emphasis on the data synchronization. A modified BP imaging method is proposed, which is suitable for direct signal synchronization scheme commonly used in spaceborne-airborne experiments. Finally, the imaging result is given with evaluation of the spatial resolution.

A polar format algorithm (PFA) as a high-efficient imaging method is widely used in bistatic spotlight synthetic aperture radar (SAR). In cases where motion error causes great defocusing in PFA images, phase gradient autofocus (PGA) is suitable for motion error compensation due to its robustness. However, a significant coupling of range-azimuth directions in bistatic SAR (BiSAR) makes conventional PGA unapplicable in PFA images. For this limitation, this letter gives the solution to the adaptability of PGA in BiSAR based on the azimuth migration correction in the wavenumber domain. The bistatic motion error is modeled, and the caused phase error is derived and analyzed. Through the wavenumber-domain analysis, the 2-D coupling is indicated still existing after polar format imaging, unlike other algorithms that utilize range cell migration correction (RCMC). Then, a phase compensation for the migration of azimuth direction is proposed to remove the 2-D coupling. Based on this, the new autofocus arithmetic flow for bistatic PFA is designed. The effectiveness of the proposed method is verified by numerical simulations.

Resolution features of spotlight SAR appear space-variant in most cases, however different in PFA. In this paper, we make analysis on the resolution features of PFA and BPA through wavenumber spectrum and draw some novel conclusions. Distinguishing from BPA, the range-Doppler contours appear parallel in the imaging domain of PFA, which makes the space-variation of the resolution features disappear. As verified by simulations, these unique phenomenon will be useful in further research on spotlight SAR.

Being capable of providing weather-independent, day-and-night, forward-looking, and high-resolution images, bistatic forward-looking synthetic aperture radar (BFSAR) is a promising sensing technique in applications such as the scene-matching-aided navigation for recently emerging high-speed maneuvering platforms (HMPs). Because of the high speed and the great maneuverability of HMPs and the bistatic forward-looking configuration, conventional image formation algorithms, such as polar format algorithm (PFA), are no longer suitable for HMP-borne BFSAR (HMP-BFSAR). Hence, in this paper, we propose a novel PFA for HMP-BFSAR image formation. In the proposed PFA, a range model, termed as quasi-continuous -move range model, is established by taking the maneuvers of the receiver during pulse propagation into account instead of adopting stop-and-go approximation. Moreover, to take advantage of the collected k -set efficiently, an affine mapping, termed as k -set affine mapping, is conceived to transform the parallelogram-shaped k -set support region to a horizontal and quasi-rectangular one. Furthermore, to compensate for the defocus effect induced by wavefront curvature, a closed-form refocus filter based on the implicit function theorem is derived. Both point target simulation and distributed target simulation are presented in this paper. The simulation results show that the proposed PFA significantly outperforms the conventional PFA in terms of focusing quality and computational efficiency when applied to HMP-BFSAR image formation.

Raw data generation of SAR echo is important for the evaluation of both imaging algorithms and SAR system design. Common time-domain echo generation methods (represented by projection method) are accurate for most of SAR modes but usually inefficient, while the existing FFT-based methods can only adapt to some relatively ideal configurations for bistatic SAR. Hence, this article will focus on FFT-based methods and try to solve the limitation of adaptability. For bistatic SAR with complicated configuration or maneuvering platform trajectories, 2-D spatial variation and difficulty on obtaining the 2-D spectrum of echo signal are the major problems to be faced with. To solve these problems, this article proposes an efficient raw data generation method based on 2-D inverse wavenumber mapping. This method first performs a 2-D FFT on the raw image to generate its 2-D wavenumber spectrum, then induces the space-variant phase using the 2-D inverse wavenumber mapping. Simulation results are presented to verify the validity of the proposed method.

Bistatic synthetic aperture radar (SAR) can provide additional observables and scattering information of the target from multiple views. In this paper, a new bistatic SAR automatic target recognition (ATR) method based on multi-input deep convolutional neural network is proposed. The geometry of the multi-view bistatic SAR ATR is modeled, and an electromagnetic simulation approach is utilized as an alternative to generate enough bistatic SAR images for network training. Then a deep convolutional neural network with multiple inputs is designed, and the features of the multi-view bistatic SAR images will be effectively learned by the proposed network. Therefore, the proposed method can achieve a superior recognition performance. Experimental results have shown the superiority of the proposed method based on the electromagnetic simulation bistatic SAR data.

Due to finite of information dimension of single bistatic synthetic aperture radar (SAR), to expand more information about ground objects we research multistatic SAR which can be decomposed into groups of bistatic SAR. It is known that scattering properties of the different viewing angles is different. In this paper, we focus on system of single transmitter and triple receivers and use polar format algorithm(PFA) to obtain images of ground objects for the triple receivers. A geometric distortion correction method is proposed due to elevation of ground objects. After the distortion correction, the three SAR images are registrated, then we put images into red, green, blue(RGB) channels respectively to realize fake color synthesis, and thus realize information fusion.