The capability to work on the high-squint mode brings greatly advantages to the Synthetic Aperture Radar (SAR) system. However, the efficient imaging of the high-squint SAR data has not been well settled. Due to the severe Range-Azimuth Coupling (RAC), the conventional imaging algorithms fail to work properly in the high-squint cases. In this paper, a Decoupled Chirp Scaling Algorithm (DCSA) is proposed for the high-squint SAR data imaging, whose key step is a Range-Azimuth Decoupling (RAD) preprocessing in the 2-D frequency domain. After RAD, the majority of the RAC is eliminated, where the high-squint SAR data is simplified into the quasi-broadside mode. The data can be then processed via the chirp-scaling-typed scheme, which is summarized as follows: The data after RAD is firstly transformed into the Range Doppler (RD) domain, in which a Non-Linear Chirp Scaling (NLCS) is performed in the range direction to eliminate the chirp rate variations caused by the residual RAC. The chirp scaling processing is simultaneously performed to equalize the Range Cell Migrations (RCM) for the full scene data. The range compression, bulk RCM correction, as well as a compensation for the cubic and quartic phases introduced by the NLCS are then accomplished in the 2-D frequency domain. Finally, the azimuth compensation is accomplished in the RD domain to obtain the final focused SAR image. Different from the Linear Range Walk Correction (LRWC) accomplished in the azimuth time domain, the RAD method proposed here does not destroy the azimuth-invariant property of the SAR echoes. Therefore, the DCSA can adapt to the wide swath SAR data imaging. Simulation shows that for the airborne SAR with 1m resolution in both range and azimuth directions, and a squint angle of 45°, the DCSA can achieve the bulk focusing of the full-scene data with a range swath of 10km, whereas the azimuth swath is not limited. Compared with the classical CSA, the DCSA requires only one more range FFT/IFFT and one more complex matrix multiplication, which is therefore timely very efficient.

Passive radar has become a research hotpot in recent years owing to the many distinctive advantages on it, such as the lightweight, radio silence and low cost. However, it targets detection performance depends largely on the choice of the radiation source. Due to the excellent global coverage, the Global Navigation Satellite System (GNSS) becomes an ideal illuminator of opportunity for the air target detection. Through the Doppler frequency modulation rate estimation (DFMR) based on the Fraction Fourier Transform (FrFT), a non-cooperative air target detection algorithm is proposed in this paper and significant improves the Signal to Noise Ratio (SNR) of the target. The experiment results are presented at last to validate the performance of the algorithm.

Global Navigation Satellite System (GNSS)-based Passive Radar (GPR) is gaining increasing attentions recently due to its potential on moving target detection (MTD). The main problem of the GPR is the low power density of GNSS signals. With the upgrades of GNSS, the total transmit power for the new launched satellites has been greatly improved. However, the total transmit power is allocated to several independent signals, which cannot be directly integrated. This paper proposes a multi-source image fusion method for the GPR which aims at coherently integrating the power allocated to different signals for the same satellite, and improving the detection performance. Validation experiments using GPS signals as illumination source and an airplane as target are conducted. The target is successfully detected by exploiting GPS L1 and L5 signals for the same satellite as illumination sources. Two-image fusion is performed utilizing the proposed method. Significant SNR improvement is achieved, which validates the feasibility of the proposed method.

The Global Navigation Satellite System (GNSS)-based passive bistatic radar (PBR) which uses the GNSS signal as the illuminators of opportunity is studied for moving target detection (MTD). GNSS-based PBR has many advantages due to the removal of the transmitting device; however, its fundamental limitation is the low power density of the GNSS signal. Therefore, the integration time should be sufficiently long to obtain a promising maximum detectable range. On the other hand, the integration time is limited by the range migration and Doppler migration of the echo caused by target motion. In this letter, a novel MTD algorithm is proposed for the GNSS-based PBR, by employing a modified radon Fourier transform (MRFT) to achieve the required long-time integration for moving targets. The MRFT integrates the echo energy via joint searching of range, Doppler, and Doppler rate of the target, which can handle not only the range migration but also the Doppler migration problems, and significantly improves the signal-to-noise ratio (SNR) of the echo signal. An experiment using the GPS L5 signal as the illumination source is conducted and a moving car is successfully detected by the proposed algorithm, although significant range migration and Doppler migration are present due to variation of its speed.

Global navigation satellite system (GNSS)-based passive bistatic radar (PBR) has many advantages benefiting from the bistatic configuration and the excellent properties of the GNSS signals. In this article, the possibility of moving target indication (MTI) using a GNSS-based PBR is analyzed and illustrated by experiments. The power budget is first evaluated to investigate the capabilities and limitations of the GNSS-based PBR. Due to the low power density of GNSS signals, long-time integration is required to achieve long-range surveillance. In our previous work, a Radon Fourier transform (RFT)-based long-time integration algorithm has been proposed for GNSS-based PBR. However, the RFT-based methods are computationally inefficient. In this article, a novel MTI algorithm based on high frame rate image sequence (HFRIS) is introduced to the GNSS-based PBR. Benefiting from the avoiding of the iterative multidimensional parameter searching, it has a higher computational efficiency than the RFT-based methods. At the same time, the possibility of multistatic positioning for moving targets using the GNSS-based PBR is analyzed. It is shown that the absolute position of the target in three dimensions could be determined if at least three satellites are utilized to measure the range delay of the target return. To confirm our analysis, experiments are conducted which detects the airplanes using the GPS signals as illuminators of opportunity. The collected data are processed by both the RFT-based method and the HFRIS-based method. Both methods have successfully detected the airplane target at a distance of about 5 km and the HFRIS-based method shows a far better performance in terms of processing efficiency. The multistatic positioning experiment is also conducted and the estimated position of the target is well consistent with the values acquired by the flight record, which shows the potential of the GNSS-based PBR on multistatic operations.

Global Navigation Satellite System Reflectometry (GNSS-R) is becoming a research hotspot in the remote sensing areas recently. This paper is focused on a new application of GNSS-R: Moving Target Indication (MTI). A modified GNSS-R based MTI algorithm is proposed. By the adding of a Doppler Frequency Modulation Rate (DFMR) estimation step, the modified algorithm could significantly improve the Signal to Noise Radio (SNR) of the target. An experiment is conducted for validation and the proposed algorithm performs well.

The co-prime-sampling SAR can effectively alleviate the contradictory relationship between spatial resolution and swath width by applying co-prime sampling in azimuth. In order to achieve accurate imaging of co-prime-sampling SAR on the condition of non-negligible range cell migration, an imaging method based on 2D sparse signal reconstruction is proposed. The 2D observed signal is intercepted and the corresponding sparse dictionary is constructed both according to the Doppler parameters of each range gate. An improved 2D signal sparse reconstruction algorithm is used to perform sparse scene reconstruction. Simulation results are provided to demonstrate the effectiveness of the proposed method for sparse scene imaging.

In recent years, electromagnetic vortex waves carrying orbital angular momentum (OAM) arouse extensive attention in remote sensing imaging fields. However, most of the researches concentrate on the staring imaging mode, where the radar is motionless relative to the targets. We establish a novel system operation mode based on the principle of synthetic aperture radar (SAR). The echo model upon this novel operation mode is established and the new imaging method modified from the back-projection (BP) algorithm is deduced. Simulation and image evaluation results demonstrate the validation of the proposed method and OAM-based SAR system can be utilized in the SAR data acquisition and signal processing fields.

The traditional particle filter detection algorithm cannot detect weak targets efficiently in the face of the current complex environment. To solve that problem, an improved particle filtering algorithm is proposed in this paper. Firstly, the basic theory of particle filter is introduced, the defects of particle filter method are pointed out. Utilizing auxiliary particle filter and resampling in filtering algorithm is proposed in this paper. So that particle degeneration can be solved which is the significant problem in particle filtering algorithm. A simulation experiment has been conducted to verify the effectiveness of the algorithm.

Global Navigation Satellite System (GNSS)-based bistatic Synthetic Aperture Radar (SAR) recently plays a more and more significant role in remote sensing applications for its low-cost, flexibility and real-time global coverage capability. In this paper, a novel high-order imaging algorithm is presented for GNSS-based bistatic SAR. Firstly, the modified equivalent squint range model (MESRM) is introduced to describe range history of the GNSS-based bistatic SAR, and the accuracy of the MESRM is analysed. Secondly, a high-order image formation algorithm based on the MESRM is derived, where the range cell migration (RCM) of the echo signal is corrected by two-step range cell migration correction (TSRCMC), and the azimuth-variance of the echo signal is solved by azimuth block hybrid correlation. Finally, simulation and experiment are performed to validate the presented algorithm.