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All pineapples are harvested manually at present in China. But manual harvesting cannot fully meet the large-scale production against the ever-increasing greying workforce. Fortunately, automatic navigation can be expected to develop the pineapple harvester. In this study, a path planning algorithm was proposed as the navigation scheme to improve the mechanization and automation level of pineapple harvesting. An improved RRT* algorithm was also used for global path planning. Firstly, the self-heuristic idea was used to constrain the generation range of sampling points. Then, the bias probability pbias was introduced to generate the random sampling points. Specifically, the sampling points were randomly generated with the probability p in the space, when p>pbias. Otherwise, the target point was used as the sampling point, in order to decrease the blindness of sampling point generation. Thirdly, the gravitational field of the artificial potential field, and the concept of direction weight were introduced in the new node expansion. The weights wg and wk were assigned to the directions of the sampling and target point, respectively, where the direction was constrained in the expansion of the new node. Fourthly, the bidirectional expansion was used to speed up the iteration speed in the double-tree expansion. Finally, the greedy algorithm was applied to prune the redundant nodes of the path. The Cantmull-Rom interpolation function was also used to smooth the path corners. Three environments (including multiple obstacles, mazes, and narrow passages) were created to simulate the path planning process, in order to evaluate the performance among the improved navigation path planning, RRT* and bidirectional RRT* algorithm. Planning time, node number, and path length were selected as the indicators. Each algorithm experimented with 30 times in every single environment. The average, maximum, minimum, and standard deviation were calculated for the simulation data of the three indicators, respectively. The simulation results showed that the average planning time of the path planning algorithm in the three environments was 17.97%, and 46.12% higher than that of the RRT* and bidirectional RRT* algorithms, respectively, while the average programming speed was 4.7, and 2.2 times as rapid as that of the RRT*, and bidirectional RRT* algorithm, respectively. Furthermore, the average node number was 87.22% and 52.52% less than that of the RRT* and bidirectional RRT* algorithms, respectively. The average path length was 3.81% and 6.08% less than the RRT* and bidirectional RRT* algorithms, respectively. The field test showed that the planning time was only 14.12% and 20.34% of the RRT* and bidirectional RRT*, respectively. The iteration number was 80.89% and 69.70% less than that of the RRT* and bidirectional RRT*, respectively. In addition, the rotation angles larger than 60° on the path planned by RRT* and bidirectional RRT* algorithms were 1.56 and 2.06 times as much as that of the improved, respectively, and the rotation angles larger than 100° on the path were 1.55 and 2.18 times. The improved RRT* algorithm can fully meet the path navigation requirements of agricultural machinery in the field. The pineapple harvester can run along the planned path to the target point as moving with the speed of 0.2, 0.4, and 0.6 m/s, but the position and heading deviation increase with the moving speed. This finding can provide a sound reference for the navigation development in agricultural machines. [ABSTRACT FROM AUTHOR]

To address the problem of single and inflexible target simulation in passive electromagnetic modulation, using the advantages of adjustable electromagnetic scattering characteristics of the active frequency selective surface (AFSS) and not actively radiating electromagnetic waves, a double-pulse periodic intermittent modulation method for switching the electromagnetic scattering state of the AFSS reflector is proposed. The double-pulse intermittent modulation signal model of AFSS reflector is constructed, and the characteristics of the modulated signal are analyzed. Through theoretical derivation, the effect of AFSS reflector on the echo matching Altering results of radar linear frequency modulation signal is investigated. Finally, simulations are performed to verify the results, which prove the effectiveness and feasibility of the proposed method. The method increases the dimensionality of control parameters and the modulation style is more abundant, which can be applied to radar target simulation to improve is variability and flexibility. [ABSTRACT FROM AUTHOR]

Aiming at the problem of low signal to noise ratio (SNR) and low probability of intercept (LPI) radar pulse waveform recognition accuracy, a radar emitter signal recognition method based on time-frequency analysis, squeeze-excitation (SE) and ResNeXt network is proposed. Firstly, the radar time domain signal is transformed into a two-dimensional time-frequency image (TFI) by Choi-Williams distribution (CWD); then, the TFI pre-processing is used to reduce the noise interference and the difference in frequency dimension location distribution, adapting to deep learning network input; finally, the TFI features are extracted by adding dilated convolution and SE structure on the basis of ResNeXt to achieve radar emitter classification. The experimental results show that when the SNR is as low as --8 dB, the overall recognition accuracy of the method for 12 types of common LPI radar waveforms can still reach 98. 08%. [ABSTRACT FROM AUTHOR]

Long-time coherent integration is one of the important techniques to improve radar detection performance. The range migration (RM), range curvation (RC), Doppler frequency migration (DFM) and Doppler frequency curvation (DFC) induced by the movement of high-speed maneuvering target during the longtime coherent integration would bring about serious integration signal-to-noise ratio (SNR) loss, which may furthermore cause the target detection performance of the radar sharp deterioration in the background of noise. In order to solve the problem, the paper proposes a parameterized long-time integration algorithm for high-speed maneuvering targets. The method applies keystone transform (KT) to eliminate linear RM firstly. Then coherently integrated modified cubic phase function (CIMCPF) and coherency integrated modified high-order ambiguous function (CIMHAF) methods are utilized respectively to estimate the first-order and second-order accelerations. Thanks to the use of signal coherent property, the method is still effective at low signal-to-noise ratio. Furthermore, since there is no brute-force search process, the computational complexity of the method is low. Simulation results and analysis demonstrate the excellent performance of the proposed method. [ABSTRACT FROM AUTHOR]

Aiming at the problem that multiple input multiple output (MIMO) radar cannot perform regular sparse array in the application of motion platforms, and the traditional sparse array optimization deign method can only optimize one object, an array structure optimization method based on multi-objective evolutionary algorithm (MOEA) is proposed. The sidelobe levels of sum beam and difference beam of MIMO radar are taken as optimization objectives, so that the system has the best possible sum beam and difference beam sidelobe suppression performance. Simulation results show that the optimal deign of MIMO radar sparse array based on MOEA with Pareto rank sorting can improve various performance of the system. [ABSTRACT FROM AUTHOR]

Considering the problems that the related evaluation index system is weakly combat-oriented, the difficulties of evaluation index quantification, and the existence of insufficient applicability of evaluation method in the research on full function operation training of radars, a combat-oriented effect evaluation method is proposed m this paper. Firstly, a combat-oriented evaluation index system is built by analyzing the combat-operation mapping relation and the full function operation procedures. The quantitative analysis of evaluation indexes is also conducted subsequently. Secondly, an evaluation model based on the group interval analytic hierarchy process (GIAHP) is built through modifying the traditional analytic hierarchy process(AHP) method using the theory of group decision-making with interval-number, and the detailed evaluation steps are also given. Finally, an example is given to verify the proposed method, the weight of each index and the evaluation result of the example are both obtained. Results show that the proposed method can solve the problem of training effect evaluation effectively, and it also provides a reference for improving the combat operator capabilities. [ABSTRACT FROM AUTHOR]

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Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

1-bit sampling has attracted extensive attention because of its advantages of low cost and low power consumption. This paper mainly discusses the pulse compression performance of radar under 1-bit sampling. Firstly, the loss of signal to noise ratio caused by 1-bit sampling is deduced, the applicable conditions of 1-bit sampling are analyzed, and it is found that 1-bit sampling is suitable for the application scenario with low signal to noise ratio of single echo. Then, through theoretical analysis, compared with high-precision pulse compression coefficient, 1-bit pulse compression coefficient will bring additional loss of pulse compression signal to noise ratio, but the implementation method is simpler. In addition, the causes of periodic false targets when the transmitted signal is linear frequency modulation (LFM) signal under high signal to noise ratio are analyzed, and it is pointed out that phase coding can effectively avoid false targets. Simulation experiments verify the correctness of the above theoretical derivation. Finally, combined with the measured data of a high frequency (HF) ground wave radar, the feasibility of 1-bit sampling is verified. [ABSTRACT FROM AUTHOR]

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Radar system environment is complex, and excessively high range sidelobes will cause weak targets to be lost and false targets. To solve this problem, a novel orthogonal frequency-division multiplexing(OFDM) radar low sidelobe waveform design method based on genetic algorithm(GA) is proposed. First, the OFDM waveform based on cyclic prefix(CP) is constructed. All sub carriers are modulated with m-sequence codes. Then, the main lobe and sidelobe ratio after pulse compression is taken as the objective function, and the phase parameter is taken as the optimization object. The objective function is transformed into an unconstrained optimization problem. Last, by using genetic algorithm to solve the optimization problem, the radar range sidelobe suppression is achieved. Theoretical analysis and simulation results show that this method can effectively suppress the range sidelobes.

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According to the remote sensing monitoring method of the ground deformation before mine landslide, the discrimination basis of the reliability of different orbit SAR data sets was proposed, and the inducing factors of landslide were analyzed. Taking the slope of the Anqian Yabaling open-pit mine in Anshan city as an example, using 44 Sentinel-1 radar images(two groups of ascending orbits and one group of descending orbit), the time series InSAR method was used to analyze the surface movement characteristics of the slope 6 months before the landslide occurred on November 25, 2019. The results show that the monitoring results obtained by different orbit data sets in the same studied area are different. The position of the top and rear edge of the landslide area showed an unusually strong acceleration within a period of time(approximately 45 days) before the landslide. The research results can provide new ideas for early identification of landslide hazard in mining areas using InSAR technology in the future. [ABSTRACT FROM AUTHOR]

Copyright of Ordnance Industry Automation is the property of Editorial Board for Ordnance Industry Automation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Copyright of Ordnance Industry Automation is the property of Editorial Board for Ordnance Industry Automation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Multi-functional radar is an indispensable and important equipment in modern electromagnetic battlefield. The interference of multi-functional radar is always a difficult problem. In this paper, based on the study of the characteristics of multi-functional radar signal and the radar countermeasure process, the method of joint representation of radar state is proposed, and the interference problem of multi-functional radar is modeled as a Markov decision process with benefits. The cognitive interference decision system is designed. The interference strategy is solved by the cognitive interference decision algorithm based on Q-learning. Through the simulation experiment, it is proved that the cognitive interference decision algorithm based on Q-learning can learn the optimal interference strategy in the absence of prior experience, have the characteristic of "cognition", and have strong adaptability in the unstable environment, which effectively supports the interference decision model mentioned above. [ABSTRACT FROM AUTHOR]

With the rapid development of electronic devices and radar systems, the electromagnetic environment has become more complex. In order to evaluate the demand of electromagnetic scattering characteristics of radar targets illuminated by multiple radiators and active devices, this paper proposes the definition, simulation methods and sample application of active radar cross section active radar cross section (ARCS). ARCS can calculate the apparent radar cross section (RCS) value observed by radar under the conditions of coherent and incoherent illumination of multiple radiators. Here, the simulation procedures of ARCS are proposed. The far field quantity required to calculate ARCS is obtained by simulation software. In case of a single incident wave, ARCS is equivalent to traditional RCS which verifies the accuracy of the ARCS calculation method. Meanwhile, the applications of ARCS are introduced by distributed coherence radar and active echo cancellation. The ARCS concept is used to evaluate the effects of active echo cancellation. Finally, the technical problems existing in current research and possible future research directions are discussed. [ABSTRACT FROM AUTHOR]

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Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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This paper presents a review of the scientific research progress of the lunar in-situ spectroscopy and radar, focusing on the important results obtained by the Chang'E-3 and Chang'E-4 missions. In terms of the spectral detection, we report the composition, the photometric characteristics, space weathering information and thermal radiation characteristics of the lunar surface. In terms of radar detection, the detection of geological subsurface structures of the Moon, the detection of possible cavities/lava-tubes, and the inversion of the dielectric properties of the lunar regolith are described. Finally, the future development trends of lunar in-situ spectroscopy and radar detection are discussed.

Objectives: Two earthquakes with a distance less than 40 km occurred in Menyuan, Qinghai Province, China, including Mw 5.9 earthquake on 26th January 2016 and Mw 6.7 earthquake on 8th January 2022. Methods: The interferometric synthetic aperture radar (InSAR) technique was utilized to process Sentinel-1A radar images from both ascending and descending tracks to retrieve high resolution coseismic surface displacement maps for these two Menyuan earthquakes. The coseismic surface displacements were then inverted to determine the fault geometry parameters and the non-uniform fault slip distributions with a dislocation model in an elastic half- space. Results: The results show that the 2016 Menyuan earthquake was a reverse event on a buried fault with a maximum surface displacement of 6.7 cm and 7.0 cm on the ascending and descending tracks, respectively. The maximum slip on the fault plane reached 0.53 m and concentrated at depths of 4 − 12 km. The 2022 Menyuan earthquake ruptured along the NWW - SEE strike with a maximum surface displacement of 78 cm in the satellite radar line of sight and a maximum fault slip of 3.5 m occurred at a depth of approximately 4 km. Conclusions: Considering the tectonic settings around the Lenglongling fault zone, the 2022 Menyuan earthquake is likely to occure in the western segment of the left‐lateral Lenglongling fault, with its western end extending westward to the Tuolaishan fault. By calculating the coulomb failure stress changes (CFS), it is inferred that the 2016 Menyuan earthquake generated considerable positive CFS which might have triggered the 2022 Menyuan earthquake. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent years, radar target recognition based on deep learning has received great attention. However, there are time constraints and resource constraints in actual combat, and the problem of small sample recognition greatly iimits its pefformance in actual recognition tasks. To solve this problem, based on the meta learning algorithm, this paper improves the performance of new tasks by learning meta knowledge from multiple related tasks, introduces the idea of tranffer learning, proposes an improved small sample learning method, and analyzes the application boundary conditions of the method through detalled performance comparison experiments. The experimental resuits based on the measured high resolution range proille data show that the pefformance advantage of meta learning method is outstanding only when there are many target categories in the historical accumulated samples and in the case of minimal samples with high correlation with the target task, the proposed method can significantly improve its comprehensive recognition performance. [ABSTRACT FROM AUTHOR]

This paper studies distributed target detection for frequency agile radars. When the synthetic bandwidth of frequency agile radars is large, radar targets become distributed targets, and thus the traditional constant false alarm rate detection methods fall. To deal with this problem, we formulaie a distributed target detection model for frequency agile radars, derive the generalized likelihood ratio rest statistic, and show the corresponding false alarm and detection rate by simulations. To improve the anti-jamming ability and the spectrum utiiization efficiency of frequency agile radars, we consider the scenario in which only parts of the frequency pouts are transmitted. Numerical results reveal that under high signal-to-noise ratio, the distributed target detection performance improves as the synthetic bandwidth increases, namely more frequency points are transmitted. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Beijing University of Technology is the property of Journal of Beijing University of Technology, Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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