Search

In this article, we propose a joint waveform based on universal filtered multicarrier (UFMC) chirp for radar jamming and communication joint systems. Modulation of radar jamming chirp signals and communication signals on different subcarrier groups in the UFMC sub-band is used to achieve the waveform design. The jamming signal in the waveform contains a frequency shift coefficient that depends on the delay time, which can effectively improve the anti-frequency hopping ability and enhance the overall jamming efficiency. Simultaneously jamming signals can provide assistance in channel estimation and equalization of communication, improving the information transmission quality of communication subsystems. We concluded through reasonable trade-off analysis that the combined weight of radar jamming and communication is closely related to the overall performance of the waveform. The simulation results show that the proposed UFMC chirp synthesized waveform has good jamming and communication performance. Software defined radio (SDR) simulation experiments demonstrated the effectiveness of this method in practical environments. [ABSTRACT FROM AUTHOR]

Multiple‐Input‐Multiple‐Output (MIMO) radar has the characteristic of multiple antenna channels, bringing on a big data volume for signal processing. Therefore, the trade‐off between detection ability and computational efficiency is always considered. In this article, an optimisation system is proposed to enhance the real‐time performance of frequency division MIMO radar without compromising accuracy. For the scenario of low‐altitude small target detection, a signal processing acceleration method is proposed and a MIMO radar optimisation system based on graphics processing unit (GPU) architecture is built. The signal model of frequency division MIMO radar is first established, improving the classical signal processing flow efficiency from the perspective of reducing fast Fourier transform (FFT) times and windowing operation times. To achieve an advanced acceleration, the parallel architecture of ArrayFire‐library in GPU is then employed. Distinct minimum parallel units are extracted by analysing the principle of digital beamforming (DBF), pulse compression, moving target detection (MTD), and constant false‐alarm rate (CFAR) algorithms. And the corresponding parallel algorithms are designed to constitute a parallel acceleration system of frequency division MIMO. Simulation results indicate that the proposed method significantly improves the efficiency of MIMO system with a maximum acceleration ratio of 65 times, meeting the real‐time processing requirements. [ABSTRACT FROM AUTHOR]

A joint communication jamming waveform is proposed in this study based on the FBMC- chirp. To increase the number of false targets in a single pulse period, the chirp signal is modulated to different subcarrier groups. Since the subcarriers of the FBMC-OQAM signal are orthogonal, the signals are naturally orthogonal. This allows the transmitter and receiver to be separated and achieve multiple false target jamming, allowing the CFAR threshold to be raised by about 20 dB and protecting the target from detection. The ratio of the frequency shift of the designed jamming signal to the frequency modulation depends on the delay time, making the joint signal more robust in response to jamming and resistant to frequency modulation. The use of intercepted radar signals allowed channel estimation, providing high-speed digital transmission while ensuring multi-false-target jamming. The simulation results show that the joint signal has jamming effects on the pulse Doppler radar. The proposed FBMC chirp joint waveform requires about 20 dB less jamming signal ratio than the existing method, and thus the energy saved can ensure the robust performance of the communication subsystem in the joint communication jamming system. The proposed system has excelled in communication rate and bit error rate performance, ensuring that instructions are accurately and completely transmitted while implementing effective jamming. [ABSTRACT FROM AUTHOR]

Since orthogonal frequency division multiplexing (OFDM) signals are sensitive to Doppler shift, OFDM signals with cyclic prefix (CP) not only reduce the communication rate but also result in symmetric pseudo peaks in the ambiguity function of the radar, which eventually lead to the degradation of the performance of the joint radar communication system (JRCS). In this study, a novel JRCS is proposed based on the filter bank multicarrier (FBMC) waveform for the inverse synthetic aperture radar (ISAR) imaging and communication system. On the one hand, FBMC waveforms are capable of low orthogonality between subcarriers, which can counter Doppler and multipath effects. On the other hand, FBMC waveforms do not require CP, so the false targets can be avoided and spectral efficiency can be improved. The influence of multipath effect and Doppler shift on FBMC waveform in an integrated system is analysed in detail, and a Doppler compensation algorithm suitable for FBMC‐integrated waveform is proposed. The phase error caused by target motion can be iteratively compensated to obtain a well‐focussed ISAR image. Finally, considering the ISAR image entropy after motion compensation as the evaluation metric, extensive simulation experiments verify the noise robustness and effectiveness of the proposed algorithm. Compared with the conventional OFDM and CP‐OFDM schemes, the simulation verifies that the proposed waveform design and processing method has better performance in the ISAR imaging and communication integrated system. [ABSTRACT FROM AUTHOR]

The data volume and computation task of MIMO radar is huge; a very high-speed computation is necessary for its real-time processing. In this paper, we mainly study the time division MIMO radar signal processing flow, propose an improved MIMO radar signal processing algorithm, raising the MIMO radar algorithm processing speed combined with the previous algorithms, and, on this basis, a parallel simulation system for the MIMO radar based on the CPU/GPU architecture is proposed. The outer layer of the framework is coarse-grained with OpenMP for acceleration on the CPU, and the inner layer of fine-grained data processing is accelerated on the GPU. Its performance is significantly faster than the serial computing equipment, and satisfactory acceleration effects have been achieved in the CPU/GPU architecture simulation. The experimental results show that the MIMO radar parallel simulation system with CPU/GPU architecture greatly improves the computing power of the CPU-based method. Compared with the serial sequential CPU method, GPU simulation achieves a speedup of 130 times. In addition, the MIMO radar signal processing parallel simulation system based on the CPU/GPU architecture has a performance improvement of 13%, compared to the GPU-only method. [ABSTRACT FROM AUTHOR]

In recent years, the rapid development of deep learning technology has brought new opportunities for specific emitter identification and has greatly improved the performance of radar emitter identification. The most specific emitter identification methods, based on deep learning, have focused more on studying network structures and data preprocessing. However, the data selection and utilization have a significant impact on the emitter recognition efficiency, and the method to adaptively determine the two parameters by a specific recognition model has yet to be studied. This paper proposes a knowledge graph-driven convolutional neural network (KG-1D-CNN) to solve this problem. The relationship network between radar data is modeled via the knowledge graph and uses 1D-CNN as the metric kernel to measure these relationships in the knowledge graph construction process. In the recognition process, a precise dataset is constructed based on the knowledge graph according to the task requirement. The network is designed to recognize target emitter individuals from easy to difficult by the precise dataset. In the experiments, most algorithms achieved good recognition results in the high SNR case (10–15 dB), while only the proposed method could achieve more than a 90% recognition rate in the low SNR case (0–5 dB). The experimental results demonstrate the efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

A novel orthogonal frequency-division multiplexing (OFDM) multiple-input multiple-output (MIMO) radar is proposed in this paper in a scenario of coexisting with a communication system. For the purpose of avoiding interference to communication while maintaining MIMO radar's capabilities, such as measuring signal's direction of departure (DOD), a collocated antenna array is divided into several overlapped subarrays. Mutually OFDM waveforms exploiting an orthogonal space-time block code are transmitted through these subarrays to obtain waveform diversity, which can be separated at the radar receiver. A MUSIC-like DOD estimation algorithm and the Cramér–Rao bound of DOD are proposed for overlapped subarrays’ configuration in order to evaluate performance of the beamforming strategy. The beamformer is designed using an optimization technique at cost of maximizing the input SNR of radar while keeping communication rate constant. Due to nonconvexity of the optimization problem, a two-step optimization algorithm is proposed. Simulation experiments validate theoretical analysis of the proposed precoding radar. Experiments also show robustness of the precoding scheme and the ability of balancing the input SNR of radar and the communication rate. [ABSTRACT FROM AUTHOR]

In the traditional model of monostatic synthetic aperture radar (SAR), the flying platform should have a uniform linear trajectory. In practice, the flight path of the SAR platform, which is highly nonlinear or curvy caused by 3-D velocity and acceleration, cannot be used in the traditional model. In this paper, a geometrical model of the monostatic SAR with general configurations is graphically illustrated by vector notation. Moreover, the gradient method is utilized to point out the effects of the motion parameters, namely, velocity vector and acceleration vector, on total bandwidth and image resolution. Based on the accurate model, a general frequency-domain algorithm, with the incorporations of pre- and postprocessing, is proposed to focus the raw data. Applicability is studied through theoretical analysis and numerical experiments. All these general analyses can be applied to different realizations of monostatic SAR mode, including spotlight SAR, sliding spotlight SAR, and Terrain Observation by Progressive Scans (TOPS) SAR. [ABSTRACT FROM PUBLISHER]