Enhancing the correlation between azimuth and Doppler frequency for speed estimation of nearby tangential targets.

With the development of intelligent transportation systems, traffic supervision radar with wide coverage plays a crucial role in traffic management and vehicle-road coordination. The correlation between Doppler frequency and azimuth has been widely validated in wide coverage traffic supervision radar for high-precision velocity measurement. However, angular glint and noise of the nearby targets lead to a decrease in correlation between the azimuth and Doppler frequency, which negatively impacts the accuracy of velocity estimation. Currently, adopting separate filtering strategies for target azimuth and Doppler frequency has limited performance in enhancing correlation. This paper presents a joint observation model for azimuth and Doppler frequency to achieve the extraction of interrelated components from subspaces, which improves the accuracy of velocity measurement. The effectiveness of this approach is validated using data obtained from X-band and Ku-band sensors.

Physical layer encryption scheme based on cellular automata and DNA encoding by hyper-chaos in a CO-OFDM system.

This study proposes an encryption scheme combining cellular automata (CA) and DNA encoding to improve security of a coherent optical orthogonal frequency division multiplexing (CO-OFDM) system, wherein key sequences are generated with good randomness and unpredictability by a 4-dimensional hyper-chaotic system. A base scrambling pseudo random binary sequence (PRBS) generated by the CA is introduced, which results in better scrambling effect and randomness in the conventional complex DNA encoding. The randomness, complexity and security of the system is enhanced due to 6 variable keys (key space of ∼10138). An experiment conducted in a 40 GHz 16QAM CO-OFDM system over an 80 km standard single mode fiber (SSMF) shows that the authorized user can successfully decrypt the received signal, while the eavesdroppers cannot derive useful information with bit error rate (BER) at approximately 0.5. An allowable optical signal to noise ratio (OSNR) penalty of 0.5 dB will be introduced to achieve same BER before and after encryption due to the error propagation of cellular automata.

A Novel MIMO-SAR System Based on Simultaneous Digital Beam Forming of Both Transceiver and Receiver.

Orthogonal frequency division multiplexing (OFDM) chirp waveform, which is composed of two or more successive identical linear frequency modulated sub pulses, is a newly proposed orthogonal waveform scheme for multi-input multi-output (MIMO) synthetic aperture radar (SAR) systems. However, according to the waveform model, there will be range ambiguity if the mapping width exceeds the maximum unambiguous width determined by the transmitted signal. This greatly limits its application in high-resolution wide-swath (HRWS) remote sensing. The traditional system divides the echoes by digital beam forming (DBF) to solve this problem, but the energy utilization rate is low. A MIMO-SAR system using simultaneous digital beam forming of both transceiver and receiver to avoid range ambiguity is designed in this paper. Compared with traditional system, the novel system designed in this paper obtain higher energy utilization and waveform orthogonality.

Automatic Regularization of TomoSAR Point Clouds for Buildings Using Neural Networks.

Tomographic SAR (TomoSAR) is a remote sensing technique that extends the conventional two-dimensional (2-D) synthetic aperture radar (SAR) imaging principle to three-dimensional (3-D) imaging. It produces 3-D point clouds with unavoidable noise that seriously deteriorates the quality of 3-D imaging and the reconstruction of buildings over urban areas. However, existing methods for TomoSAR point cloud processing notably rely on data segmentation, which influences the processing efficiency and denoising performance to a large extent. Inspired by regression analysis, in this paper, we propose an automatic method using neural networks to regularize the 3-D building structures from TomoSAR point clouds. By changing the point heights, the surface points of a building are refined. The method has commendable performance on smoothening the building surface, and keeps a precise preservation of the building structure. Due to the regression mechanism, the method works in a high automation level, which avoids data segmentation and complex parameter adjustment. The experimental results demonstrate the effectiveness of our method to denoise and regularize TomoSAR point clouds for urban buildings.

A Novel Orthogonal Waveform Separation Scheme for Airborne MIMO-SAR Systems.

In recent years, multi-input multi-output (MIMO) synthetic aperture radar (SAR) systems, which can promote the performance of 3D imaging, high-resolution wide-swath remote sensing, and multi-baseline interferometry, have received considerable attention. Several papers on MIMO-SAR have been published, but the research of such systems is seriously limited. This is mainly because the superposed echoes of the multiple transmitted orthogonal waveforms cannot be separated perfectly. The imperfect separation will introduce ambiguous energy and degrade SAR images dramatically. In this paper, a novel orthogonal waveform separation scheme based on echo-compression is proposed for airborne MIMO-SAR systems. Specifically, apart from the simultaneous transmissions, the transmitters are required to radiate several times alone in a synthetic aperture to sense their private inner-aperture channels. Since the channel responses at the neighboring azimuth positions are relevant, the energy of the solely radiated orthogonal waveforms in the superposed echoes will be concentrated. To this end, the echoes of the multiple transmitted orthogonal waveforms can be separated by cancelling the peaks. In addition, the cleaned echoes, along with original superposed one, can be used to reconstruct the unambiguous echoes. The proposed scheme is validated by simulations.

Three-Dimensional Imaging Method for Array ISAR Based on Sparse Bayesian Inference.

The problem of synthesis scatterers in inverse synthetic aperture radar (ISAR) make it difficult to realize high-resolution three-dimensional (3D) imaging. Radar array provides an available solution to this problem, but the resolution is restricted by limited aperture size and number of antennas, leading to deterioration of the 3D imaging performance. To solve these problems, we propose a novel 3D imaging method with an array ISAR system based on sparse Bayesian inference. First, the 3D imaging model using a sparse linear array is introduced. Then the elastic net estimation and Bayesian information criterion are introduced to fulfill model order selection automatically. Finally, the sparse Bayesian inference is adopted to realize super-resolution imaging and to get the 3D image of target of interest. The proposed method is used to process real radar data of a Ku band array ISAR system. The results show that the proposed method can effectively solve the problem of synthesis scatterers and realize super-resolution 3D imaging, which verify the practicality of our proposed method.

A Novel Scheme for MIMO-SAR Systems Using Rotational Orbital Angular Momentum.

The vortex electromagnetic (EM) wave with orbital angular momentum (OAM) brings a new degree of freedom for synthetic aperture radar (SAR) imaging, although to date, its application to multi-input multi-output (MIMO) SAR has not yet been widely reported. In this paper, an orbital angular momentum (OAM)-based MIMO-SAR system is proposed. The rotational Doppler Effect (RDE) of vortex EM waves offers a novel scheme for an OAM-based MIMO-SAR system. By transmitting the rotational vortex EM waves, echoes of different OAM modes can be discriminated by a bandpass filter in the range-Doppler domain. The performance of the proposed scheme is independent of the time-variant channel responses, and the wider beam width of the vortex EM waves delivers, for the same antenna aperture size, better performance in terms of swath width and azimuth resolution, in contrast to the plane EM waves. Moreover, the spatial diversity of vortex EM waves shows great potential to enhance the MIMO-SAR system applications, which involve high-resolution wide-swath remote sensing, 3-D imaging, and radar-communication integration. The proposed scheme is verified by proof-of-concept experiments. This work presents a new application of vortex EM waves, which facilitates the development of new-generation and forthcoming SAR systems.