Search

In order to improve the accuracy of precise classification of vegetation points and ground points using LiDAR point cloud data in dense forest terrain, five traditional filtering methods were used to evaluate the filtering accuracy of forest area point cloud, and the corresponding initial filtering was carried out with the help of cloth simulation filtering algorithm. After accurate processing, the initial ground points with relatively complete terrain features were obtained. Then, the iterative opening calculation was carried out on the initial ground points with prominent vegetation points, and the new ground points were obtained. And with the aid of a series of indicators such as Class Ⅰ error and Class Ⅱ error, the accuracy of scientific evaluation was determined. Compared with the traditional filtering algorithm of Class Ⅱ, the total error of the cloth simulation algorithm and simple morphology algorithm decreased significantly, and the Kappa coefficient showed an increasing trend. The results showed that this method was suitable for point cloud classification in forest area and can obtain better filtering effect. [ABSTRACT FROM AUTHOR]

In order to study the waveform selection of radar seeker in the terminal guidance and tracking phase, this paper proposes a waveform selection algorithm in the guidance and tracking process of cognitive radar seeker. Firstly, we establish the processing flow of radar seeker waveform selection by combining the seeker guidance and observation filtering models; Secondly, we use the interactive multiple model unscented Kalman filter (IMMUKF) algorithm to solve the nonlinear tracking problem. We minimize tracking error by searching for waveform parameters based on the maximum mutual information criterion. The simulation results show that the waveform selection algorithm can effectively improve the seeker tracking accuracy and provide stable guidance overload. [ABSTRACT FROM AUTHOR]

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]

A beam dwell time allocation algorithm based on Riemannian manifolds is proposed for the spatial search process of digital array radar. In order to compensate for the gain loss resulting from beam broadening as it scans angles of the broadside，the spatial distribution of beam dwell time in uv-plane is given according to Riemannian manifolds. The dwell time is allocated optimally over the whole space and the transmitting power of beam is minimized under the condition that the one detection probability and the cumulative detection probability of the specified range are satisfied. The simulation results show that the beam dwell time allocation algorithm based on Riemannian manifolds eliminates the effect of beam gain variation caused by the change of direction，and realizes the equal power detection in different directions. [ABSTRACT FROM AUTHOR]

Today, Sentinel ‐ 1A data with terrain observation with progressive scanning (TOPS) imaging mode is increasingly used in earth observation aiming at consistent monitoring of surface change and its deformation. However, due to the limited accuracy of coarse co ‐registration, spectral aliasing along the azimuth direction enables the presence of phase jumping in overlapping area of neighboring bursts. Although geometrical co‐registration in conjunction with enhanced spectral diversity (ESD) is proven to be a feasible strategy to correct such error and has been widely used in some open source softwares (e.g. DORIS (Delft object‐oriented radar interferometric software), SNAP (sentinel applications platform), ISCE (InSAR scientific computing environment)), the performance of ESD is still not satisfactory and relies strongly on spatiotemporal decorrelation. Given that decorrelation is generally quantized by interferometric coherence, this paper presents and assesses a new methodology to improve the accuracy of ESD by fully exploring the high coherent targets. Specifically, this method focuses on mitigating the spatiotemporal decorrelation in fine coregistration procedures by: (1) Selecting stable targets with moderate and high coherence using accurate coherence estimation. (2) Maximizing coherence magnitude by optimal interferometric subset chosen from Dijkstra algorithm. We compare and test this method against current favorites based on single master image and network‐based enhanced spectral diversity (NESD), and the experimental results demonstrate the value of our method. It can make up for the shortage of NESD method. [ABSTRACT FROM AUTHOR]

For multiple-input multiple-output over-the-horizon radar( MIMO-OTHR),the minimum variance distortionless response( MVDR) is usually used to solve the impact of the ionospheric multimode clutter in the received echo on the detection of the target. The output signal-to-clutter-plus-noise ratio( SCNR) of traditional MVDR algorithm is low due to the omnidirectional emission of MIMO-OTHR,the inaccurate estimation of interference-noise covariance matrix,and a few training samples within a finite coherent accumulation time. Therefore,the MVDR algorithm is improved to enhance the multimode clutter suppression ability of MIMO-OTHR. A transmit beamspace preprocessing is realized by a second order cone programming( SOCP) to focus the energy on the principal mode angle,which is the transmit angle of the target path reflected by the ionosphere. The echo signal received by array is spatially smoothed to suppress the expected signal of principal mode and improve the estimation accuracy of interference-noise covariance matrix. A bi-iterative MVDR beamforming algorithm based on the beamspace preprocessing is proposed to reduce the computational load and the requirement of training samples. Simulated results show that the improved MVDR algorithm can be used to effectively suppress multi-mode clutter,and obtain higher output SCNR with fewer training samples and less computational load. [ABSTRACT FROM AUTHOR]

Adaptive waveform optimization technology is one of the key technologies of cognitive radar， which can improve the performance of radar systems. For the target detection， an adaptive waveform design method based on dual mutual information (DMI) criterion was proposed in the clutter environment. The mutual information (MI) was maximized by the proposed method between the received signal and the target impulse response while the mutual information could be minimized between the received signal and clutter impulse response. With the transmitted signal energy constraint， the optimization model for optimal waveform was established， and the optimal waveform was solved by the maximum marginal allocation algorithm (MMA). The simulation results demonstrate the validation of the proposed method. [ABSTRACT FROM AUTHOR]

The traditional paramctcr-bascd signal sorting system cannot adapt to the problem of radar signal sorting in the current complex situation, and the blind source separation algorithm based on independent component analysis (ICA) is introduced into the radar signal sorting algorithm. FastICA algorithm combines fixed-point iteration and non-Gaussian maximization algorithm. It lias the advantages of good stability, fast convergence and small calculation. However, this algorithm is very sensitive to noise and cannot be performed with low SNR. Aiming at this shortcoming, a synchronous cumulative average noise reduction algorithm is introduced. and signal equalization and smoothing to improve the original algorithm are combined, so that the new algorithm can sort the radar signals with low SNR. Simulation results show that the improved algorithm can achieve good sorting effect under low SNR and retain the advantages of the original algorithm. [ABSTRACT FROM AUTHOR]

Three-dimensional phase unwrapping is one of the key steps of time-series interferometric syn- thetic aperture radar (InSAR) technology. The unwrapping results directly affect the accuracy of time-series InSAR land subsidence monitoring. Aiming at the problem of the whole period unwrapping error caused by phase undersampling in areas with serious land subsidence and large change of terrain slope, a weighted least squares phase unwrapping algorithm based on frequency confidence is proposed, which replaces the weighted least squares phase unwrapping algorithm based on phase gradient in the time-dependent three-di- mensional phase. By improving the accuracy of phase slope change estimation, the accuracy and stability of spatio -temporal three-dimensional phase unwrapping can be improved. The land subsidence results of the typical area in Beijing are obtained by using the improved spatio-temporal three-dimensional phase unwrap- ping method. Compared with the classical spatio - temporal three - dimensional phase unwrapping method, the improved method can obtain higher accuracy of land subsidence monitoring results. Especially for the subsidence funnel region where the slope changes greatly and the decorrelation exists obviously, the subsid- ence monitoring accuracy has improved significantly. [ABSTRACT FROM AUTHOR]

To meet the requirements of accuracy and reliability of plant protection robot in ridge identification and route planning, also improve the working conditions of farmers, and achieve an unmanned operation purpose, an algorithm based on multi-support-vector proportioning weight of SVM (support vector machine) to identify the ridge line of vineyards, and the path planning of plant protection robots were proposed. The strategy first uses Kalman filter to pre-process coarse orchard data information obtained by Lidar scanning. According to the principle that Kalman filter complies with Gaussian distribution, the prior point between 2 adjacent points was taken as the prior state, and the latter point was used as the observed point to obtain posteriori state estimation, so as to realize data integration and analysis. With its good system state estimation characteristics, the collected data can be used to judge the trend of the ridge line, so as to correct the noise outliers in the data and improve the readability of the data. Then according to the characteristics of the vineyard branch ridge and the characteristics of ridges line with clearly separable spacing, and corresponding to the situation that the ridge line on both sides can be completely separated, the method was combined with SVM linear classification. With the unique advantages of the classification and due to that SVM can search the unique segmentation hyperplane, the maximum interval and segmentation hyperplane, classification margins in the ridge environment could be gotten. The split hyperplane obtained at this time would be between ridge lines. However, there was a big deviation from the angle of the direction of the ridge line and the horizontal distance. It could not meet the precise operation requirements of plant protection robots. It needed further data processing and analysis. In order to obtain accurate position of the center of ridge line, finally, the relative weights were assigned to the sample points of each ridge based on the geometric interval relationship between the sample points on both sides of the ridge and the corresponding SVM classification marginal line. The classification marginal line was reformed according to the number of sample points and the relative weights. According to the condition of the product of the interval relationship between each sample point and the classification margin, their relative weight must be consistent with the quality value of classification margin. The random sampling consistency iteration method (RANSAC) would avoid the error of cost estimate, and could estimate the parameters of the mathematical model from a group of observed data with outliers, so as to obtain the predicted safety location of the ridge. Although the pre-estimated security location of ridge line was not necessarily consistent with the actual location of the vineyard ridge, navigation line could be obtained indirectly by the security ridge line on both sides and the principle of angle bisector which could meet the requirements of precision operation of plant protection robot. Operation guidance line for plant protection robot could be acquired. After a number of actual samples were tested, the average angular deviation between the fitted navigation line and the actual ridge centerline was 0.72°, and the average distance deviation of the relative plant protection robot was 4.22 mm. Experimental results showed that this algorithm could effectively identify and locate the navigation route needed by the plant protection robot. The fitted navigation line could meet the requirements of accurate operation of the plant protection robot in the vineyard. However, the redundancy of the algorithm was relatively large, and the time required to process data in a single time was about 2.05 s. With the accelerated calculation speed of the processor in the future, the algorithm provided in the article can provide a reference solution for such a problem. [ABSTRACT FROM AUTHOR]

When the interference enters from the direction of the main-lobe of the radar, adopting the adaptive beamforming algorithm will lead to problems such as beam distortion and migration of the main-lobe. Aiming at the problem of interference entering from the radar main-lobe, this paper proposed an anti-jamming method based on the design of the transmitted waveform. When the signal encoded by Frank is transmitted, it constructed the matched filter and the blocking filter by using the orthogonality of the Frank code, and passed the received data through the two filters to obtain two signals. Then it suppressed the interference by the adaptive cancellation method, thus suppressed the main-lobe interference. Finally, simulation results show that the method of waveform design can effectively suppress interference from main-lobe entry. [ABSTRACT FROM AUTHOR]

To deal with the parameter estimation problem in multi-function radars( MFR) based on stochastic context-free grammar( SCFG) model,this paper developed a new method of MFR parameter estimation problem based on Earley parsing called EIO algorithm on the basis of traditional inside-outside( IO) algorithm and viterbi-score( VS) algorithm. This method pre-processed the intercepted radar data by combining IO algorithm with Earley parsing to handle arbitrary grammar production rules. It utilized the EIO algorithm to realize the learning of grammatical production rules probabilities and MFR parameter estimation. Theoretical analysis and simulation results show that the modified algorithm can reduce the computation complexity,memory complexity and running time while keeping the same level of estimation accuracy,validates the correctness and effectiveness of this method. [ABSTRACT FROM AUTHOR]

A novel phase-comparison sum-difference monopulse radar angular glint modeling algorithm based on deterministic model is proposed by analyzing the shortage of conditional angular glint deviation models based on energy flow tilt theory and wave front distortion theory. The number of scattering dots and the parameters of radar can be set in this model, and the echo signals of summing channel and differential channel needed by angle measurement verification can be obtained. Theoretical analysis and simulation results show that the novel model is more accurate for the large deviation angle of each scattering point. This model is more conducive to the simulation of angular glint suppression algorithm. [ABSTRACT FROM AUTHOR]

A method which discriminates the coherent dual-source angle deception interference by using the relative difference between the co-polarization and cross-polarization components of target and interference is proposed. A model of mono-pulse polarization radar echo is established, and the co-polarization and cross-polarization echoes of the sum and difference beams are obtained. A statistic to distinguish the existence of coherent dual-source interference is constructed by using the difference between the interference and the radar target response function in the different polarization channels. A certain confidence level threshold is given according to the measured data of typical warhead and aircraft target and the simulation of coherent dual-source interference. The measured data obtained in darkroom and the computer simulation show that the algorithm is feasible and valid. [ABSTRACT FROM AUTHOR]

The radar data of multi-period is regarded as binary image by the gaining enlightenment from the man-made track initiation method. A track initiation algorithm is proposed based on the Hough transform and dilation on morphology to improve the efficiency of track initiation methods under heavy- clutter environment. Firstly a pre-processing method is proposed to filter the image and to delete the false alarm point based on the association gate formed by the maximum velocity and the radar scan period. An approximate method is proposed to describe the distribution of the target position by analyzing the effect of measurement error on target position. And then the structural element is formed to dilate the binary image so as to emphasize the linear characteristic of the true tracks. Hough transform is used to detect the lines on the binary image. The simulation experiment presents the output of each step, and the results show the efficiency of the proposed pre-processing method and the initiation algorithm. [ABSTRACT FROM AUTHOR]

Aiming at tracking maneuvering target of surface movement radar (SMR) for the advanced surface movement guidance and control system (A-SMGCS), the variable structure interacting multiple model (VS-IMM) algorithm is used in the system. Firstly, according to the real movement of aircraft, a constant velocity motion model is established, as well as a constant acceleration motion model and a constant turn motion model. Then, considering the defects of the fixed structure interacting multiple model (FS-IMM) algorithm, the VS-IMM algorithm is applied to the airport surface movement target tracking by combining with the airport map. Finally, VS-IMM and FS-IMM algorithms are designed by extended Kalman filtering (EKF), and they are compared through computer simulation. Simulation results show that VS-IMM algorithm is more reliable than IMM algorithm on tracking accuracy. So VS-IMM algorithm has the greater value on surface maneuvering target tracking. [ABSTRACT FROM AUTHOR]

The Multiple-Input Multiple-Output (MIMO) radar was proposed in recent years. Using MIMO radar to detect the location of multi-target, a lot of algorithms are failure when the multi-target echo signals are coherent. Concerning this problem, a localization algorithm of coherent multi-target is presented in bistatic MIMO radar. The algorithm constructs virtual array for both the transmit and receiver array to de-correlate the coherent multi-target echo signals, and then the location of multi-target can be obtained. The estimated parameters are automatically paired without additional paring computation. The proposed method avoids the array aperture loss and the performance of angle estimation is improved. Theoretical analysis and simulation results verify the effectiveness of this method. [ABSTRACT FROM AUTHOR]