Spaceborne bistatic synthetic aperture radar (BiSAR) plays an important role in the field of remote sensing. However, frequency deviation among different oscillators will cause a modulated phase error on the echo signal. Therefore, phase synchronization is a necessary condition for the normal operation of BiSAR. Currently, the main synchronization schemes are pulsed alternate synchronization of radio frequency(RF). However, these schemes have problems such as complex synchronization hardware links, interruption of SAR imaging, and constraints on swath width coverage. This paper proposes a monochromatic continuous wave duplex synchronization with azimuth phase coding (APC). The synchronization signal is a monochromatic continuous wave at intermediate frequency (IF), sharing the same IF bandwidth with the echo signal. Both the synchronization signal and the echo signal are received simultaneously by the satellite and separated using APC techniques. By employing IF continuous wave for synchronization signal, the hardware design of the synchronization link is simplified. Operating at IF allows for a wider antenna beam, which in turn simplifies the configuration of the synchronization antennas and reduces the number of required antennas. The processing workflow of the synchronization scheme is described in detail. The simulation experiments are performed. The accuracy of phase synchronization can reach 1 degree, which verifies the effectiveness of the proposed synchronization scheme.

The phase synchronization is a necessary condition for the normal operation of spaceborne multistatic synthetic aperture radar (SAR). The research on bistatic SAR phase synchronization is relatively mature, and some phase synchronization schemes have been verified in practical systems. Because of the limitations that existing synchronization schemes extended to the case of multistatic SAR, this letter proposes a phase synchronization scheme for spaceborne multistatic SAR. As the scheme suggests, we used orthogonal frequency-division multiplexing (OFDM)-Chirp signal to be the synchronization signal and exploited the orthogonality of subcarriers to separate the mixed synchronization signal. The decomposed signals are independently compressed to extract phase error. This scheme can simultaneously achieve phase synchronization for multiple radar platforms on the basis of satisfying the high accuracy of phase synchronization, greatly improves the efficiency of phase synchronization. Furthermore, the performance prediction and phase synchronization simulation for this synchronization scheme are presented, which verifies the feasibility of the proposed scheme.

Geosynchronous orbit (GEO) satellites are widely used in communications and navigation fields due to their special properties, such as comprehensive ground coverage and fixed subsatellite trajectories. The safety of GEO satellites can be ensured by using space-borne inverse synthetic aperture radar (SBISAR) to achieve high-precision observations or monitoring of uncatalogued targets near the GEO satellites. However, the amount of echo data is significant due to the slow relative motion between the GEO targets and SBISAR during long coherent processing intervals (CPIs). In this work, a variable sampling start echo receiving method is proposed to reduce the amount of redundant echo data, and the timing which combining the radar tracking with imaging is designed. First, the Earth center inertial (ECI) coordinate position vectors of the GEO target can be obtained through the monopulse method and coordinate transformation. Second, the initial orbit parameters of the GEO target are established by the Gibbs method. Third, the slant range of the GEO target is obtained by the interacting multiple model (IMM). Finally, the slant range is used to design the sampling start of the echo window and the timing of tracking imaging integration. Taking GEO satellite imaging as an example, experiments based on simulation data verify the effectiveness of the proposed method.

The performance of traditional translational motion compensation methods is degraded when migration through range cell (MTRC) occurs or the echo amplitude is time-varying. In this letter, an effective translational motion compensation approach is proposed for high-resolution inverse synthetic aperture radar (ISAR) imaging with time-varying amplitude. The proposed algorithm based on the minimum mean square error (MMSE) criterion and the energy extraction of prominent point can realize the translational motion compensation accurately. First, the observation time is divided into multiple sub-apertures, and the range alignment of the echoes within each sub-aperture is achieved. Then, the range alignment between sub-apertures is realized based on the MMSE criterion. The Radon transform is performed on the range-aligned echoes to extract the prominent point with the maximum energy, and the envelope fine alignment and phase correction are realized. After rotation compensation, a well-focused ISAR image is obtained. Simulation experiments and real measured data demonstrate the effectiveness of the proposed algorithm.

An important challenge in high-resolution inverse synthetic aperture radar (ISAR) imaging of maneuvering targets is the 2-D spatial-variant (SV) high-order phase error. The classic autofocusing phase correction method cannot effectively correct the SV phase error, which makes it difficult for the traditional range-Doppler (RD) algorithm to obtain high-quality images in high-resolution imaging. The range SV phase error can be compensated for each range cell separately after migration correction of the cross-range cell, but correcting the azimuth SV phase error is challenging. This article presents a high-resolution ISAR imaging algorithm for maneuvering targets with azimuth adaptive partitioning and phase compensation function estimation. First, the coarse-focus image is obtained by the azimuth Fourier transform (FT) after translational motion compensation and migration through range cell (MTRC) correction. Then, the azimuth coarse-focusing result is adaptively partitioned at each range bin. Each partitioned data block is transformed into the time domain, and joint time-frequency analysis (JTFA) is performed to obtain the time-frequency curve of the signal. Through alignment of time-frequency curves, the phase compensation function is inverted. Finally, the corrected subblocks are stitched together to obtain high-quality ISAR images. ISAR imaging experiments with simulated and real data demonstrate the effectiveness and practicability of the proposed algorithm in high-resolution ISAR imaging of maneuvering targets.

With the development of IoT techniques, urban computing has become an emerging topic in academia and industry. The goal of urban computing is to address some issues of urban planning by using the big data generated in urban facilities. The massive trajectory data processing is viewed as an important issue in urban computing. To satisfy the storage and processing requirements of massive trajectory data, a distributed system is usually adopted. However, existing distributed systems face challenges of data locality aware partitioning and various trajectory queries. In this paper, we propose a distributed framework of massive trajectory data analysis based on HBase, to realize spatio-temporal query more effectively. We first design a temporal-based pre-partitioning strategy to improve the performance of data written. Then we develop a Multi-Level Index to speed up the process of spatio-temporal query. Extensive experiments on real trajectory datasets demonstrate that the proposed framework significantly improves efficiency and usability.

Vector Processing is an efficient way to exploit data-parallel with wide data operations, which is widely employed by wireless baseband signal processing. However, wide data operations also cost much more power and lead to high power consumption especially for vector register file (VRF). To resolve this issue, firstly, we profiled the read/write characteristics of LTE baseband signal algorithms to VRF and found three facts exist: a lot of copy or movement operations are sourced from vector load/store, the occasions for concurrent access to all VRF read/write ports are little and a large number of short-lived values exists. Based on these observations, a buffer-aided VRF is presented to exploit these characteristics for low power. The experiment results show: The proposed buffer-aided VRF can effectively reduce the vector copy and movement cost comparing with general register file architectures and also achieve better power saving effects than similar buffering technologies. A reduction of 40.9% power dispassion over centralized VRF can be reached in register file level with negligible performance loss.

This letter presents a new filtering technique for interferometric synthetic aperture radar (InSAR) phase images. Traditional local denoising algorithms all suffer from the drawback of removing texture detail information. In contrast, several nonlocal methods have attained good performance in InSAR applications. However, these methods only take radiometric similarity. The patch-based locally optimal Wiener filter (PLOW) utilizes both geometrically and radiometrically similar patch information by clustering analysis and nonlocal filtering; thus, it can better balance between detail preservation and denoising. Nevertheless, PLOW itself is not fitted for InSAR. In this letter, we modify and improve the original algorithm while considering the coherence coefficient and the characteristics of InSAR. This new method provides better filtering results, but with a higher computational cost. Moreover, we introduce the box dimension in fractal geometry as a new index. Experiments on simulated and real data demonstrate that this algorithm outperforms traditional denoising methods.

MapReduce based data-intensive computing solutions are increasingly deployed as production systems. Unlike Internet companies who invent and adopt the technology from the very beginning, traditional enterprises demand easy-to-use software due to the limited capabilities of administrators. Automatic job optimization software for MapReduce is a promising technique to satisfy such requirements. In this paper, we introduce a toolkit from IBM, called MRTuner , to enable holistic optimization for MapReduce jobs. In particular, we propose a novel Producer-Transporter-Consumer (PTC) model, which characterizes the tradeoffs in the parallel execution among tasks. We also carefully investigate the complicated relations among about twenty parameters, which have significant impact on the job performance. We design an efficient search algorithm to find the optimal execution plan. Finally, we conduct a thorough experimental evaluation on two different types of clusters using the HiBench suite which covers various Hadoop workloads from GB to TB size levels. The results show that the search latency of MRTuner is a few orders of magnitude faster than that of the state-of-the-art cost-based optimizer, and the effectiveness of the optimized execution plan is also significantly improved.

A new operating mode of synthetic aperture radar (SAR), referred to as Mosaic mode, can simultaneously obtain high azimuth resolution and wide swath. In Mosaic mode, the radar beam scans in the range direction while the strip line is advanced by steering antenna beam in the azimuth direction. The imaging bursts constituting Mosaic mode have the same acquisition geometry with squint spotlight mode. When the steering angle is large, the effect of the skew of two-dimensional (2-D) spectrum cannot be neglected. In this paper, a modified two-step approach is proposed to focus the data of Mosaic mode. It can remove the azimuth spectrum folding effect caused by the skew of the 2-D spectrum. Simulation results confirm the validity of the proposed algorithm.

Compared with SAR interferometry(InSAR), polarimetric SAR interfermotry(PolInSAR) acquires plenty information to estimate parameters, and on the other side, the penetrability of low frequency electromagnetic wave is better than high frequency. So an accurate retrieval of the topography can be implemented from low frequency quad polarimetric SAR interfermotry on the basis of the Random Volume over Ground (RVoG) scattering model abstractly. But there is no paper validation about this theory with experiment data from quantitative point of view. In this paper, analysis and comparison of the quantitative topography accuracy between InSAR and PolInSAR, between X-band PolInSAR and L-band PolInSAR are presented firstly with data validation. Simulated data are used to prove the validity.

In order to reap the potential benefits that waveform diversity can provide for spaceborne synthetic aperture radar remote sensing, echoes from different subpulses constituting a complete transmit waveform should be effectively separated at first. This paper presents a new separation approach implemented by an advanced null-steering beamformer on satellite. Compared with common null-steering beamforming, our approach will take into account the characteristics of echo signal from the scene and accordingly embed the finite-impulse response (FIR) filtering process into the modified null-steering beamformer to deal with the issue of pulse extension. In this paper, echo signals generated by multidimensional encoded waveform will be analyzed in detail; based on this analysis, FIR filter and the new null-steering beamformer are derived. Simulation results show that much better separation performance can be obtained by our approach than by conventional null-steering beamforming.

The combination of space-time waveform encoding and digital beamforming (DBF) has been proposed as a novel concept to improve the performance of synthetic aperture radar (SAR) systems in the future. In this paper, we research one such new operational mode to reduce azimuth ambiguity in high-resolution wide-swath SAR image and present the processing scheme based on 2-D DBF for this mode. The main procedures and techniques are described in detail, and a complete mathematical derivation of the scheme is given; furthermore, a sample SAR system is provided, from which numerical simulation results are obtained to justify our derivations. In addition, an in-depth analysis of system performance associated with this mode, from the perspectives of both azimuth ambiguity-to-signal ratio (ASR) (AASR) and range ASR (RASR), is carried out. It is shown that a meaningful improvement of AASR can be attained at a small cost of raised RASR level, as compared with the performance of single-input multiple-output SAR.