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In recent years, deep learning has been widely used to solve the bottleneck problem of synthetic aperture radar (SAR) automatic target recognition (ATR). However, most current methods rely heavily on a large number of training samples and have many parameters which lead to failure under limited training samples. In practical applications, the SAR ATR method needs not only superior performance under limited training data but also real-time performance. Therefore, we try to use a lightweight network for SAR ATR under limited training samples, which has fewer parameters, less computational effort, and shorter inference time than normal networks. At the same time, the lightweight network combines the advantages of existing lightweight networks and uses a combination of MnasNet and NetAdapt algorithms to find the optimal neural network architecture for a given problem. Through experiments and comparisons under the moving and stationary target acquisition and recognition (MSTAR) dataset, the lightweight network is validated to have excellent recognition performance for SAR ATR on limited training samples and be very computationally small, reflecting the great potential of this network structure for practical applications., Comment: 6 pages, 3 figures, published in 2023 IEEE Radar Conference (RadarConf23)

Accurate and effective semantic segmentation methods for remote sensing are important for applications such as precision agriculture, urban planning, and disaster monitoring. Convolutional neural networks (CNN) have achieved remarkable performance in the field of remote sensing semantic segmentation. However, the design of CNNs is both time-consuming and necessitates a substantial amount of domain expertise and experience. To address the aforementioned issues, we propose a neural architecture search method called EAS-CNN. The method constructs a search space based on a U-shaped structure and utilizes a fixed-length encoding solution based on gene expression suppression to preserve potential useful information during the evolution process. Furthermore, an improved genetic strategy is proposed to enhance search efficiency and save computational resources. In this paper, we evaluate the proposed EAS-CNN method against state-of-the-art semantic segmentation methods and verify its effectiveness. Experimental results show that EAS-CNN achieves high OA values of 91.2% and 91.6% on the Vaihingen and Postman datasets, respectively. Furthermore, we conduct a thorough analysis of the experimental results and summarize effective design patterns for model architecture to enhance remote sensing semantic segmentation tasks.

IntroductionLung cancer has the highest rates of morbidity and mortality among all cancers. Patients with lung cancer inevitably confront psychosocial discomforts and progressively experience depression and anxiety that potentially impact the clinical outcomes [e.g., quality of life (QoL)]. These mental disorders in patients with lung cancer may effectively be alleviated with prescribed Chinese traditional mind-body exercises. This study aimed to determine the effect of the exercise prescription containing Chinese traditional mind-body exercise on QoL, depression, and anxiety in patients with lung cancer.MethodsIn this study, 52 patients with non-small cell lung cancer (NSCLC) recruited from the China-Japan Friendship Hospital were divided into two groups, namely, the experimental group (N = 26) and the control group (N = 26). The experimental group was treated with an 8-week exercise prescription containing aerobic and resistance training. The control group received the usual care during the study period. The QoL, depression, and anxiety were separately investigated using EORTC QLQ-C30, EORTC QLQ-LC13, the Self-Rating Depression Scale (SDS), and the Self-Rating Anxiety Scale (SAS) at baseline and post-intervention. The scores of questionnaires were analyzed using the paired sample and independent sample t-tests to explore the intragroup and intergroup differences, respectively.ResultsThe EORTC QLQ-C30 scores for physical functioning, role functioning, emotional functioning, and global QoL in the experimental group at post-intervention were significantly higher than those at baseline. The EORTC QLQ-C30 scores for fatigue, pain, dyspnea, and insomnia in the experimental group at post-intervention were significantly lower than those at the baseline. The SDS scores (baseline: 57.74 ± 8.77 vs. post-intervention: 51.42 ± 7.31, p < 0.05) and the SAS scores (baseline: 56.63 ± 9.39 vs. post-intervention: 49.16 ± 7.83, p < 0.05) in the experimental group at post-intervention were significantly lower than those at baseline.ConclusionsThe 8-week exercise prescription containing moderate-intensity Baduanjin (5 days per week) can effectively alleviate QoL, depression, and anxiety in patients with NSCLC. Our exercise prescription is an effective supportive treatment for lung cancer patients with depression and anxiety.Clinical trial registrationChinese Clinical Trial Registry (ChiCTR1900025121).

OBJECTIVE: To confirm the anti-NPC effect of sanguinarine (SA) through a series of wet experiments. METHODS: NPC cell viability was determined by proliferation experiment. Cell clone formation experiment, cell scratch test, transwell migration and invasion experiment and flow cytometry-based cell apoptosis assay were further performed. In addition, Western blotting was performed to investigate the cell signaling pathway. All the relevant experimental data were statistically processed using SPSS 16.0 software. RESULTS: The results showed that sanguinarine represented a time and dose dependent inhibition effects on NPC cell proliferation including the low differentiated CNE2 cells and high metastatic 5-8F cells, along with the cell cloning ability reduction. In addition, sanguinarine has a certain inhibitory effect on the invasion and migration of NPC cells. Mechanistically, sanguinarine displayed the anti-NPC effects mainly involved into the suppression of mTOR signaling and cell apoptosis, which is closely associated with the tumor growth and metastatic malignancy. CONCLUSIONS: Collectively, we discover that sanguinarine is a new high-efficiency anti-NPC monomer of Chinese medicine, with a value for the follow-up pre-clinical research.

As the main problem of the durability deterioration of concrete structures, the corrosion of steel bars is usually made by the method of electrified corrosion with a short cycle and low cost. However, there is a big difference between the actual corrosion depth and the theoretical corrosion depth after the reinforcement is electrified. In this paper, through the accelerated corrosion test of steel bars, the change law and influence factors of corrosion efficiency of steel bars in concrete simulated pore solution and NaCl solution are studied. The test results show that the corrosion efficiency of reinforcement in the NaCl solution is higher than that in the concrete simulated pore solution, and the corrosion efficiency in the NaCl solution changes in two stages with the corrosion degree of reinforcement. The corrosion efficiency of concrete in the simulated pore solution decreases with the increase of corrosion degree of reinforcement, which is more significant than that in the NaCl solution. Under the same conditions, the corrosion efficiency is higher in the chloride ion solution with high concentration, and the influence of chloride ion concentration change in the simulated pore solution of concrete on the corrosion efficiency is more significant. The corrosion efficiency of reinforcement under low current density is higher than that under high current density.

Recent transformer-based solutions have been introduced to estimate 3D human pose from 2D keypoint sequence by considering body joints among all frames globally to learn spatio-temporal correlation. We observe that the motions of different joints differ significantly. However, the previous methods cannot efficiently model the solid inter-frame correspondence of each joint, leading to insufficient learning of spatial-temporal correlation. We propose MixSTE (Mixed Spatio-Temporal Encoder), which has a temporal transformer block to separately model the temporal motion of each joint and a spatial transformer block to learn inter-joint spatial correlation. These two blocks are utilized alternately to obtain better spatio-temporal feature encoding. In addition, the network output is extended from the central frame to entire frames of the input video, thereby improving the coherence between the input and output sequences. Extensive experiments are conducted on three benchmarks (Human3.6M, MPI-INF-3DHP, and HumanEva). The results show that our model outperforms the state-of-the-art approach by 10.9% P-MPJPE and 7.6% MPJPE. The code is available at https://github.com/JinluZhang1126/MixSTE., Comment: CVPR2022 Accepted Paper

Event camera is an emerging bio-inspired vision sensors that report per-pixel brightness changes asynchronously. It holds noticeable advantage of high dynamic range, high speed response, and low power budget that enable it to best capture local motions in uncontrolled environments. This motivates us to unlock the potential of event cameras for human pose estimation, as the human pose estimation with event cameras is rarely explored. Due to the novel paradigm shift from conventional frame-based cameras, however, event signals in a time interval contain very limited information, as event cameras can only capture the moving body parts and ignores those static body parts, resulting in some parts to be incomplete or even disappeared in the time interval. This paper proposes a novel densely connected recurrent architecture to address the problem of incomplete information. By this recurrent architecture, we can explicitly model not only the sequential but also non-sequential geometric consistency across time steps to accumulate information from previous frames to recover the entire human bodies, achieving a stable and accurate human pose estimation from event data. Moreover, to better evaluate our model, we collect a large scale multimodal event-based dataset that comes with human pose annotations, which is by far the most challenging one to the best of our knowledge. The experimental results on two public datasets and our own dataset demonstrate the effectiveness and strength of our approach. Code can be available online for facilitating the future research.

Unmanned aerial vehicle (UAV) can provide superior flexibility and cost-efficiency for modern radar imaging systems, which is an ideal platform for advanced remote sensing applications using synthetic aperture radar (SAR) technology. In this paper, an energy-efficient passive UAV radar imaging system using illuminators of opportunity is first proposed and investigated. Equipped with a SAR receiver, the UAV platform passively reuses the backscattered signal of the target scene from an external illuminator, such as SAR satellite, GNSS or ground-based stationary commercial illuminators, and achieves bi-static SAR imaging and data communication. The system can provide instant accessibility to the radar image of the interested targets with enhanced platform concealment, which is an essential tool for stealth observation and scene monitoring. The mission concept and system block diagram are first presented with justifications on the advantages of the system. Then, a set of mission performance evaluators is established to quantitatively assess the capability of the system in a comprehensive manner, including UAV navigation, passive SAR imaging and communication. Finally, the validity of the proposed performance evaluators are verified by numerical simulations.

Spatial Description Resolution, as a language-guided localization task, is proposed for target location in a panoramic street view, given corresponding language descriptions. Explicitly characterizing an object-level relationship while distilling spatial relationships are currently absent but crucial to this task. Mimicking humans, who sequentially traverse spatial relationship words and objects with a first-person view to locate their target, we propose a novel spatial relationship induced (SIRI) network. Specifically, visual features are firstly correlated at an implicit object-level in a projected latent space; then they are distilled by each spatial relationship word, resulting in each differently activated feature representing each spatial relationship. Further, we introduce global position priors to fix the absence of positional information, which may result in global positional reasoning ambiguities. Both the linguistic and visual features are concatenated to finalize the target localization. Experimental results on the Touchdown show that our method is around 24\% better than the state-of-the-art method in terms of accuracy, measured by an 80-pixel radius. Our method also generalizes well on our proposed extended dataset collected using the same settings as Touchdown., Comment: Accepted at NeurIPS 2020; Peiyao Wang and Weixin Luo made equal contribution

Super-resolution imaging of real beam scanning radar is of great significance in many military and civil fields. And iterative shrinkage-thresholding algorithm (ISTA) is one of the most popular methods. However, its convergence speed is very slow. Many accelerated schemes have been proposed to solve this problem. In this paper, ISTA and several typical acceleration methods of ISTA are analyzed, and the performance of these algorithms is compared through simulations.

Hand exoskeletons for rehabilitation usage are devices for helping the stroke patients who are suffering from hand function disabilities. The present hand exoskeleton devices are cumbersome and too big in size, and are inconvenient in patients' daily life because of lacking of portability and reliability. In this paper, a new type of portable hand exoskeleton device is proposed to solve such problems as mentioned above. Issues such as the experimental setup, the mechanical design, the system configuration of the hand exoskeleton device are introduced, and evaluations toward motion characteristics are also be discussed.

To determine whether students using mind maps would improve their performance in a final examination at the end of lecture-based pharmacology course.Aquasi-experimental study.Kunming Medical University, from September 2014 to January 2015.One hundred and twenty-two (122) third year undergraduate medical students, starting a 48-hour lecturebased pharmacology course, volunteered to use mind maps as one of their study strategies (intervention group), while the remaining 100 students in the class continued to use their usual study strategies (control group) over the duration of the course. The performance of both groups in the final course examination was compared. Students in the intervention group also completed a questionnaire on the usefulness of mind maps during the course and in preparation for the final examination.The students' performance of intervention group was superior to performance of the control group in all parts of a multi-modal final examination. For the multiple choice questions and comprehensive scores, average marks of 45.97 ±7.22 and 68.07 ±12.77, respectively were acquired by the control group, and 51.77 ±4.95 (p0.01) and 80.05 ±7.54 (p0.01), respectively by the intervention group. The median IQR scores for "filling in the blanks" questions, short answers questions and case analyses, were 6.00 (6.00), 8.00 (3.50), 8.75 (5.88), respectively for the control group, and were all significantly higher at 8.00 (4.00) (p=0.024), 10.00 (2.00) (p0.001), and 11.00 (3.25) (p=0.002), respectively for the interventiongroup. Questionnaire responses showed that 95.45% thought that mind maps helped them to prepare more efficiently for the final exam; 90.91% believed that mind maps helped them to better understand all of pharmacology. Ninety-one percent also thought that mind maps would help them to better understand other disciplines, and 86.36% students would like the lecturers to utilize mind mapping as an alternative to conventional teaching formats, such as the use of Power Point.The addition of mind maps to students' study of pharmacology at Kunming Medical University improved their performance in all aspects of a multi-modal final examination.

This paper discusses the antenna phase center trajectory (APCT) design for the "one-active" linear-array 3D imaging SAR (LASAR). First, we discuss the principle of the one-active LASAR and demonstrate its feasibility by experiment. To describe the 3D spatial resolution of the one-active LASAR, the relationship between the 3D ambiguity function (AF) of the one-active LASAR and the system parameters is discussed in detail. Based on the analysis, we divide the APCT design into three topics: the direction of the linear array, the length of the linear array, and the switching mode of the active element [named as antenna phase center function (APCF)]. On the first topic, we conclude that, when the range, along-track, and cross-track directions are orthogonal to each other, the ambiguity region of the one-active LASAR attains minimum, and the 3D spatial resolution can be separated into the range, along-track, and cross-track resolutions. On the second topic, we find that the cross-track resolution is determined by the length of the linear array and the frequency of the carrier. To ensure that the length of the linear array is acceptable, the carrier should be W-band wave or millimeter wave. On the third topic, the effect of APCF is researched, and we find that both the periodic APCF and the pseudorandom APCF can produce 3D resolution, except for the periodic rectangle APCF. For the pseudorandom APCF and the periodic APCF with short period, the cross-range 2D AF is or can be approximated as the product of two 1D AFs in the along- and cross-track directions. Finally, the distribution of the pseudorandom APCF is optimized by the Lagrange multiplier method under the minimum variance criterion, and we find that, when the pseudorandom APCF obeys the parabolic distribution, the cross-range 2D AF is optimal.

This letter concerns the resolution-fusion method for linear array 3-D imaging SAR (LASAR). Limited by the length of the linear array, the cross-track resolution of LASAR is often lower than that in the along-track direction. To overcome this disadvantage, we assume that there are two LASAR systems whose trajectories are orthogonal to each other. Thus, we obtain a row low-resolution image and a column low-resolution image of the same scene. Using the orthogonal complement decomposition technique, we fuse the two images into one quasi-high-resolution image. Moreover, we find that the fusion distortion is unavoidable and contains the high-frequency component in both row and column directions. The information loss ratio is (N - 1)2/N 2 (N denotes the ratio of low resolution to high resolution). For a smooth image, the energy loss ratio is near to zero. With the increase of the noise energy, the energy loss ratio increases correspondingly. When the noise submerges the image completely, the energy loss ratio converges to the information loss ratio.

A complete method of synchronization technology of bistatic radar using global position system (GPS) is presented. The pulse per second signal (1PPS) is elaborately modified to increase the time synchronization precision and keep loop locking. A very high time synchronization precision is achieved. Using the modified 1PPS to discipline the local OCXO, the reference frequency signal achieves both high long term stability (LTS) and short term stability (STS) properties. An algorithm, named phase abrupt change CFAR is presented to restrain the 1PPS phase abrupt change and keep loop locking. The experimental results indicate that this time and frequency synchronization method is effective and the time synchronization precision of the synchronization system can be improved from ± 100 ns to ± 25 ns. In addition, the phase noise is improved to 20 dB.

Passive millimeter wave (PMMW) images inherently have the problem of poor resolution owing tolimited aperture dimension. Thus, efficient post-processing is necessary to achieve resolution improvement. Anadaptive projected Landweber (APL) super-resolution algorithm using a spectral correction procedure, which at-tempts to combine the strong points of all of the projected Landweber (PL) iteration and the adaptive relaxationparameter adjustment and the spectral correction method, is proposed. In the algorithm, the PL iterations are im-plemented as the main image restoration scheme and a spectral correction method is included in which the calculatedspectrum within the passband is replaced by the known low frequency component. Then, the algorithm updatesthe relaxation parameter adaptively at each iteration. A qualitative evaluation of this algorithm is performed withsimulated data as well as actual radiometer image captured by 91.5 GHz mechanically scanned radiometer. Fromexperiments, it is found that the super-resolution algorithm obtains better results and enhances the resolution andhas lower mean square error (MSE). These constraints and adaptive character and spectral correction proceduresspeed up the convergence of the Landweber algorithm and reduce the ringing effects that are caused by regularizingthe image restoration problem.

Along with the development of the starch and grain‐alcohol industries, biomass energy production has recently become important. Cassava is an important biomass energy plant. In this paper, geographic information system (GIS) and remote sensing (RS) are used, along with a knowledge of the growing environment needed for cassava and the farmland and ecology protection policy of China, to evaluate the cassava growing potential of Winning County. The processing of spatial data is done first. Then, the evaluation principles are defined according to the spatial data and the required growth conditions. The evaluation data are obtained by spatial data analysis according with the evaluation principles. Lastly, the cassava planting potential results are verified by referencing these to cassava planting statistical data for 2005 provided by Nanning City Government of Guangxi province. This paper provides the science basis for Wuming County to develop local grain‐alcohol and biomass energy industries.

Aimed at solving the distance and velocity decoupling problems of a moving target in LFMCW radar signal processing, a multiple repetition frequency waveform is adopted and a Doppler frequency duster algorithm is proposed, which is capable of recovering true velocity from the coupled velocity estimation directly. For the resolution of multiple targets, a match algorithm based on mean square error is also proposed. The combination of the above two methods realizes distance and velocity decoupling of multiple moving targets. The result of simulation verifies the effectiveness of the methods, the velocity estimation performance of DFS algorithm is improved by 2.5 dB compared with Chinese remainder theorem.

Optimization of land use structure consists of economic and social and ecological optimization. Applying the minds of system engineering and principles of ecology, this paper presents such thoughts: the optimal forest-coverage rate calculated according to the reality of a district is set as main standard of ecological rationality in the district; through considering the value of ecosystem services of the land with GREEN equivalent (mainly cultivated land and grassland) and based on the rule, GREEN equivalent, this paper introduces the area conversion between woodland and cultivated land, also between woodland and grassland; this paper establishes a multi-dimension controlling model of optimization of land use structure. In addition, a multi-objective linear programming model for optimization of land use structure is designed. In the end, this paper tests and verifies this theory of ecological optimization, taking Qionghai city in Hainan Province as an example.

The experimental result of two-dimensional imaging of an airfield object by LFMCW millimeter-wave radar is presented. The configuration of the radar system and the techniques used in the system, including frequency sweep linearization, system background rejection, dynamic range compression and segments processing, are presented.

This paper presents the system design and experimental results of a 35GHz coherent LFM-CW radar for use in near range two-dimensional imaging. Special techniques, including FM sweep linearization, range-segment processing, system background voltage suppression and dynamic range compression are also presented.

In this paper, a novel image fusion algorithm based on Nonsubsampled Contourlet Transform (NSCT) and image segmentation is proposed, for the application of Passive Millimeter Wave (PMMW) concealed objects detection. PMMW and visual images are fused to get a better presentation of original images, maintaining both visual background and concealed object detected in PMMW images. This algorithm combines the extraction of Region of Interest (ROI) and the NSCT based fusion. The experimental results show that the proposed algorithm has better fusion performance compared with traditional methods.

In this paper, the effect of platform movement on the echo signal of forward-looking imaging radar is studied through establishing accurate echo signal model. Based on the geometric relationships between platform movement and beam scanning, the mathematical expressions of instantaneous scanning velocity, the illumination starting time and lasting time are derived. Through analyzing the accurate echo signal model, it is found that platform movement causes imaging target's deviation from the actual location and pattern distortion. At last, simulations demonstrating this effect are carried out. This paper provides theoretic basis for forward-looking radar imaging data processing. (5 pages)

Spotlight SAR accumulates large Doppler bandwidth to improve azimuth resolution. On condition of certain pulse reputation frequency (PRF), Doppler bandwidth accumulates at the cost of imaging scene. This is a classic tradeoff between azimuth resolution and scene size in spotlight mode. A novel algorithm is proposed here to break the restriction. Firstly, a deramping based method is presented through bulk data processing to finish azimuth Fourier transform under low PRF. Omega-k algorithm is then applied to focus the full image. This algorithm is free of classic restriction and requires PRF only larger than the instantaneous bandwidth. Its bulk data processing is efficiency with no sub-aperture or interpolation. In this case, this algorithm is qualified to wide scene spotlight SAR imaging. The effectiveness of this algorithm is demonstrated by point target simulation.

Angular resolution is the key parameter of radar. Conventional means of increasing angular resolution are dependent on the size of the antenna aperture. In framework of maximum likelihood, this paper presents an iterative algorithm to restore the target location information and then to obtain angular superresolution. Theoretical analyses indicate that algorithm accelerates convergence speed and achieves angular superresolution efficiently, and computational burden is relatively small. Simulation results show that the algorithm can efficiently attenuate the effect of antenna pattern convolution and highly enhance angular resolution; test data results show an order of improvement in angular resolution over real aperture image, also confirm that the method could obtain angular superresolution.

Aiming at the problem that information source of similarity measure is limited to image intensity usually in multi-polarization SAR registration, we propose an improved Mutual Information(MI) based on the multiple correlation information between the same polarized channels (HH, W) in multi-polarization SAR images. In this method, by analyzing the correlation characteristics of three polarized channels in multi-polarization SAR, and using channel correlation information extracted from polarimetric covariance matrix, we compute MI in multi-polarization SAR to improve the similarity measure. Finally, the simulation results show that, in the multi-polarization SAR image registration, similarity measure information sources affect the performance of similarity measure. We compare the similarity measures with different information sources in curve sharpness and noise immunity. The results prove that the measure based on the correlation of the same polarized channels for multi-polarization SAR performs excellently.

This paper concerns the compensation of known trajectory deviations in spaceborne/airborne bistatic SAR (SA-BSAR). And the motion compensation technique is effectively incorporated with the high-precision frequency domain imaging processing for SA-BSAR. Simulation results validate the proposed motion compensation method.

Time-frequency rate distribution (TFRD) indicates the characteristics of instantaneous frequency rate (IFR) of a signal. This paper proposed a method based on time-frequency rate distribution to estimate Doppler frequency rate by analyzing the linear frequency-modulated (LFM) characteristics of synthetic aperture radar (SAR) echo in the azimuth direction. This method can be applied to low signal-to-noise ratio (SNR) situation with high estimation precision. Simulation and practical results show the effectiveness of the method.

A simulation procedure founded on SGI Onxy4 visualization system and SGI OpenGL Performer™ visualization development toolkit was discussed; a scene graph in accordance with its node configuration motion and man-machine interaction simulation were designed; based on OpenGL Performer, a transforming algorithm for scene graph object moving simulation was studied; the interaction rules between scene objects, the event triggering and feedback method of the simulation procedure was discussed and designed; and finally, separately took examples by a virtual man interaction module, a numerical lathing-milling machining center and a mud-water balanced tunnel boring machine, three operation instances for moving simulation and interaction were programmed and realized.

“One-active” LASAR is a kind of linear array 3-D image SAR system that only one element of the linear array is active at every footprint. To verify the feasibility of “one-active” LASAR, two X-band transmitter and receiver antennas are mounted on a 2D motion control system. Then, we control the antennas moving with a specific trajectory to synthesize a virtual sparse 2D antenna array. Finally, the back-projection algorithm is employed to reconstruct the RCS distribution of the 3-D observation scene. The 3D imaging results of “one-active” LASAR are present to demonstrate the feasibility of “one-active” LASAR.

For the detecting moving target, an Improved Viterbi Algorithm (IVA) is a useful technique for a Track Before Detect (TBD) architecture implementation, designed to track and detect dim maneuvering targets from an image sequence under low signal-to-noise ratio(SNR) conditions. It especially suits real passive millimeter wave (PMMW) as the objects radiant energy is very weak. The IVA does a search over all the possible state sequences, marking probable tracks by scanning each pixel in each frame, and determining where it was likely to originate from in the previous image. In this paper the real time calculation of detecting threshold and the IVA process is described. The experimental results show that the IVA performs well for dim PMMW image sequences at low SNR environment with complex background.

In this paper, based on research the principle of the focal plane array (FPA) in passive millimetre wave (PMMW) imaging, we present a spatial-variant image mathematical model by introducing the focal-image plane transformation operator and spherical projection geometrical relationship and non-uniform Multiple-Beam Antenna (MBA) model. This model can express separately the process of the propagation and the accumulation and receive which are the space variable factors of three different attributes on the effects of the imaging quality. Based on analysis FPA PMMW imaging model and space-variant characteristics analysis, we present a spherical anti-projection transformation method to eliminate space-variant characteristics of the PSF and geometric correction processing. (4 pages)

A signal processing method is presented in order to solve the problem of measurement error caused by wide terrain fluctuation within antenna's wide beam and the range-velocity coupling problem caused by platform's high velocity. A signal processing method and height detecting algorithm is proposed in this paper to implement height measurement. The beat spectrum is processed by intercepting and weighing to solve the measurement error problem mentioned above, and the coupling problem is solved by pairing between positive and negative sweeping frequency. Certain measurement accuracy is achieved by the method. The effectiveness of the method is validated through simulation results. (4 pages)

This paper concerns resolution-fusion method for linear array 3-D imaging SAR (LASAR). Limited by the length of the linear array, the cross-track (CT) resolution of LASAR is often lower than that in the along-track (AT) direction. To overcome this disadvantage, we assume that there are two LASAR systems whose trajectories are orthogonal to each other. Thus, we obtain a row-low-resolution image and a column-low - resolution image of the same scene. Using the orthogonal complement decomposition technique, we fuse the two images into one quasi-high-resolution image.

Generalized principal component analysis integrating class information (ICGPCA) is proposed for feature extraction in this paper. Firstly we compute wavelet coefficients of images using DB2 wavelet and extract the approximate sub-image of wavelet transformation, and then extract the feature of the sub-image using ICGPCA which maximizes the between-class scatter and minimizes the within-class scatter. Experimental results adopting nearest neighbour classifier (NNC) and support vector machine (SVM) classifier show that the proposed method can extract effective features with lower dimensions, consequently enhance the correct probability of recognition and decrease the recognition computation effectively. The recognition rate without target azimuth information arrives at nearly 97%. (4 pages)

Images acquired from passive millimeter-wave (PMMW) radiometer have poor resolution due to limited aperture dimension. Therefore, super-resolution algorithm (SRA) is a key component for PMMW imager. SRA realizes spectrum extrapolation, however, spectrum in-band is deteriorated too. Wiener-Richardson-Lucy algorithm (WRLA) recovers spectrum in-band by Wiener filter, and extrapolates spectrum out-of-band by Richardson-Lucy algorithm (RLA). WRLA can avoid spectrum deterioration in passband, but its ability for spectrum extrapolation is limited also. We propose an improved algorithm to solve this problem. This algorithm, which has built constraints according to characteristics of PMMW imaging, uses projection-onto-convex-sets (POCS) technique to enhance the WRLApsilas performance, so it is termed as POCS-WRLA.

Model the output echo power from the matched filter of airborne radar receiver. Based on the same pulse time width, the same transmitted power and the same radar operation scene, signal-clutter-noise power ratio of the matched filter output is presented, and some new results different from the intuitionistic viewpoints is put forward. The impact of signal bandwidth on airborne radar echoes and target detector is discussed in detail. At last, computer simulations about typical airborne radar operation scene provide the verification and analysis.

In this paper, we present a fast 3-D imaging method for linear antenna synthetic aperture radar (LASAR). The basic idea of this technique is to consider the 3-D SAR imaging problem as tracing a surface in the observation region, since a great deal of 3-D image region contains no scatterer (such as atmosphere) or is shadowed by the other scatterers. The steps of the fast 3-D imaging method includes: Initiation, prediction, searching and recursion. Finally, some numerical experiments are presented to demonstrate the feasibility of this method. And we find that the computational cost of the fast 3-D imaging method varies according to the fluctuation of ground, and is about a dozen of times larger than that of 2-D BP algorithm.

This paper discusses the antenna phase centre trajectory (APCT) design for the sparse linear array 3-D imaging SAR(LASAR). Firstly, we introduce the signal model of the sparse LASAR. Based on the model, we discuss the 3-D ambiguity function (AF) of the sparse LASAR, and reveal the relationship between the 3-D AF and the system parameters. Finally, the distribution of the pseudo-random APCF is optimized by the Lagrange multiplier method under the minimum variance criterion, and we find that when the pseudo random APCF obeys the parabolic distribution, the cross-range 2-D AF attains optimal, which has both good mainlobe and sidelobe performance.

A compact passive mm-wave imager (PMMW) has been developed for imaging with 3 mm Dicke-Radiometer and will be reported here. It uses a single-channel scanned superheterodyne radiometer. To solve the contradiction of sensitivity and spatial resolution for the motive platform imaging, adjustable integrator was designed and wavelet-analysis was adopted to wipe off noise effectively. To test a close range and different plane for imaging, two set antenna was designed for imaging. The parameters of the radiometer are given below: the center frequency 91.5 GHz, the system band-width 4 GHz, the sensitivity 0.5 K, the linearity 0.9999.

A solution for the approximated two-dimensional spectrum's analytical expression of spaceborne/airborne hybrid BSAR is presented. To overcome the difficulty of resolving analytical solution for the system's stationary phase point, the two-dimensional spectrum's phase is approximated by two-order Taylor expanding around the point, which is not only in the neighborhood of the system's corresponding stationary phase point but also can be obtained analytically. Thus the spaceborne/airborne hybrid BSAR system response's approximated spectrum is pretty close to the actual one and can be expressed analytically. Taking TerraSAR-X as transmitter and PAMIR as receiver, the phase error caused by the approximation is simulated for different point targets in the image scene, and the simulated echo of point target is focused by the approximated two-dimensional spectrum. The simulation results demonstrate the validity of the proposed solution.