133 results about "Ground moving target" patented technology

A system is disclosed in which a geographic area of interest can be selected, and information corresponding to the selected area can be downloaded and displayed by a user in an efficient and timely manner. The geographic area of interest may initially be selected by various input means such as a map, longitude / latitude coordinates, a global positioning system (GPS), and the like. Once the particular geographic area has been selected, geographic information corresponding to the selected area is downloaded to the user. The geographic information may include photographic images, radar, radio transmission, cell phone transmission, time sequenced images, ground moving target information, air moving target information, maritime moving target information, red or blue force identification and / or potential hazard areas information. The geographic information may be stored in a suitable data storage system such as a server. Alternatively, the geographic information may be generated real time and downloaded to the user. In one embodiment, the geographic information includes photographic images and a relatively low resolution image of a large geographic area is initially displayed to the user. The user can then select a limited region of the photographic image for closer viewing. The limited region of the photographic image may then be downloaded to the user in a higher resolution format, thereby reducing the amount of high resolution data that must be transmitted to the user. Various display devices may be used, such as personal data assistants (PDAs), laptop computers, desktop computers, vehicle-mounted computers, tablets, cell phones and the like. The display device may also be used as the input device to both select the geographic area of interest and display the photographic images or other geographic information of the selected area.

The invention discloses an unmanned aerial vehicle system and a method for dynamically positioning a ground moving target, belonging to the fields of unmanned aerial vehicle system application and the like. The unmanned aerial vehicle system comprises an unmanned aerial vehicle body, a vehicle-mounted photoelectric rotating tower and a ground control terminal, wherein the unmanned aerial vehicle body comprises an acquisition device, the vehicle-mounted photoelectric rotating tower comprises a photoelectric sensor and a sight-stabilizing platform, and the ground control terminal comprises a determining device, a trace command generating device, a resolving device and a predicting device. According to the technical scheme provided by the invention, geographical coordinate information including latitude, longitude and the like of a tracked ground moving target can be output in real time, the original geographical coordinate information can be accurately and quickly fitted, the moving trend of the ground moving target can be predicted and evaluated, and the original geographical coordinate information can be screened to realize display and prediction of the track of the moving target; the positioning accuracy acquired by the unmanned aerial vehicle system and the method approaches that of static positioning and can meet requirements for initial alignment of weapons including artilleries and the like, and the probability of fusion processing of an unmanned aerial vehicle intelligence system and an entire-army intelligence gathering network is provided.

The invention discloses a ground moving target imaging method for a single-channel synthetic aperture radar (SAR). The method comprises the following steps of: (1) correcting distance curvature; (2) correcting distance migration; (3) estimating Doppler parameters; (4) estimating motion parameters; (5) compressing a direction; and (6) repeating the steps until all moving targets are processed. In the invention, the distance curvature of moving target echo data is corrected by second-order Keystone transform, so the method has the advantage of high-resolution SAR data imaging; by uniformly correcting the distance curvature of all stationary targets and all moving targets, the defect of large computation amount in the prior art is overcome; and by building a second-order moving target imaging model, parameter estimation and imaging of maneuvering moving targets can be performed, and the moving states of the moving targets can be more accurately described from aspects of speed, acceleration and the like.

The invention relates to a low-attitude tracking system of unmanned aircraft on ground movable target and relative method. Wherein, said system comprises carrier system and ground system; the carrier system is formed by camera, table, carrier image sender and carrier data transmitter; the ground system is formed by image receiver, image collector, PC, and ground data transmitter; the tracking method comprises that extracting target via threshold value division, calculating out the position of target gravity center to find its position in track field, and manually interfering the track state. It uses several threshold values, which can be replaced to improve the track stability. The invention has high real-time property and stability.

The invention discloses a local-area joint-dimension-reduction range ambiguity clutter suppression method based on an FDA-MIMO radar so that problems that the existing range ambiguity clutter suppression method has the poor detection performance, the operation load is high, and the requirement on the independent and identically distributed samples is high can be solved. The method comprises: stepone, carrying out matching and filtering on echo data of a radar by using a transmitting waveform; step two, carrying out range dependence compensation on the matched filtered data; step three, constructing a local-area joint dimension reduction matrix and performing dimension reduction on the received data; step three, on the basis of data after dimension reduction, estimating a clutter covariance matrix; step four, on the basis of a minimum variance, non-distortion response to a wave beam forming device is carried out to obtain an optimal weight vector; step five, carrying out weighting on the data after dimension reduction by using an optimal weight, suppressing a range ambiguity clutter, and detecting a target signal. Compared with the existing range ambiguity clutter suppression method, the provided method has the following advantages: the computing complexity is low; the requirement on the independent and identically distributed samples is low; and the clutter suppression performance is good. The range ambiguity clutter suppression on an airborne radar is realized. The method can be applied to ground moving target detection of an airborne radar.

The invention discloses an expansion method of an interference phase of multi-baseline interference synthetic aperture radar. The process is that a SAR imaging processing is carried out respectively to M echo data received by a satellite; any one of the images after the SAR imaging processing is selected as a main image; by using the main image as a reference, a rough registration is carried out respectively to other images through a correlation method so as to obtain M-1 roughly-registered SAR images; A roughly-registered SAR image is used for constructing an optimum weighted joint data vector jx (i, w); a covariance matrix Cov (i, w) is estimated according to the optimum weighted joint data vector and resolved characteristically so as to obtain a cost function; the interference phase phi corresponding to the minimum value of the output power of the cost function is used as the deployment result of the interference phase; the above-mentioned relevant process is repeated respectively to each of pixels to obtain the expansion result of the interference phase of the entire image. The expansion method disclosed by the invention has the advantages of small calculating amount and accurate expansion of the interference phase when the SAR image registration accuracy is bad, thereby being used for the reconstruction of a ground three-dimensional terrain with high resolution and high precision and the detection of a ground moving target.

The invention provides a ground moving target detection and parameter estimation method. The technical scheme realizes the moving target detection and two-dimensional velocity estimation by combining with an interference image sequence with multiple sub-bands and sub-apertures on the basis of a three-way ultra-wide bandwidth (UWB) synthetic aperture radar (SAR) image. The specific steps of the method are as follows: 1, generating a sub-band sub-aperture image sequence; 2, generating a sub-band sub-aperture interference image sequence; 3, detecting the moving target; and 4, estimating the two-dimensional velocity of the moving target. By using the ground moving target indication and parameter estimation method provided by the invention, the moving target and a static target can be distinguished on an imaging position and a phase position; the radial velocity of the moving target can be estimated clearly; and the azimuth speed and distance speed can also be estimated.

The invention discloses a bistatic forward-looking synthetic aperture radar ground moving target detecting method and imaging method. The detecting method includes the steps of firstly, utilizing Bulk-Deramp filtering to eliminate Doppler blurs and reducing space variations of the Doppler rate; secondly, utilizing first-order Keystone conversion to complete range migration correction of a static target and a ground moving target; then, utilizing extended orientation nonlinear frequency modulation and frequency scaling operation to equilibrate the Doppler rate of the static target; meanwhile, enabling the Doppler rate of the ground moving target to be different from the Doppler rate of the static target; finally, building a second-order fuzzy function product, completing detection on the ground moving target and estimating the Doppler rate of the ground moving target. The problem that the moving target and the static target are hard to distinguish when BFSAR is under a background with strong clutter is solved. According to the imaging method, after the detection on the ground moving target is completed, an echo of the moving target is focused by using the estimated Doppler rate of the ground moving target, and then imaging the ground moving target is completed.

The invention discloses a space arbitrary configuration distributed SAR moving target parameter estimation method based on a cancellation accumulation space-time spectrum and relates to the distributed SAR ground moving target parameter estimation method. The method is used for solving the problems of great impacts caused by signal-to-noise ratio and waste of information when the existing SAR multi-channel processing method carries out parameter estimation, and the specific process of the method is as follows: 1) establishing an extended space-time model of space arbitrary configuration distributed synthetic aperture radar echo signals according to the super-sparse distribution and the high-speed flight characteristic of a spaceborne distributed SAR; 2) taking a conjugate of the extended space-time model obtained in the step 1) as a cancellation factor, and utilizing the space-time accumulation method for establishing an objective function; and 3) utilizing the objective function obtained in the step 2) to carry out the moving target parameter estimation on multi-source signals of the space arbitrary configuration distributed SAR. The method is applicable to the distributed SAR moving target parameter estimation.

An aircraft-based infrared image recognition device for a ground moving target, including an infrared non-uniformity correction module, an image rotation module, an image registration module, a multi-level filtering module, a connected domain labeling module, a target detection and feature recognition module, a process control module, and a FPGA-based interconnection module. The invention uses an ASIC / SoC chip for image processing and target recognition, the DSP processor and the FPGA processor, it is possible to enable a multi-level image processing and target recognition algorithm, to improve system parallel, and to facilitate an aircraft-based infrared image recognition method for a ground moving target. Meanwhile, embodiments of the invention effectively reduce power consumption of the device.

Aiming at a multi-channel single SAR (Synthetic Aperture Radar) platform and for analyzing the influence of the baseline length to the moving target indication, the invention discloses an antenna design method of multiple baselines and a corresponding multi-channel ATI (Along Track Interferometry) universal algorithm is elicited. By utilizing the baseline design method, the flexibility in selecting the baselines in a system is improved, the moving target indication performance is improved according to different demands, and abundant interference phase information is provided for later processing; and the ATI universal algorithm in match with the antenna design method is applicable to all multi-channel GMTI (Ground Moving Target Indication) systems of which the antenna mode is that one is used for transmitting and multiple for receiving, and a phase filter mode involved is simple and effective, so that the ATI universal algorithm has good university and strong practicability.

The invention discloses a method for steadily classifying a ground moving target based on super-resolution Doppler spectrum, and mainly solves the problem that the classification performance is low because the signal structure is influenced during clutter reduction, the resolution ratio is low under short residence time and the noise cannot be suppressed in the conventional similar method. The method comprises the following steps of: calculating a short-time echo signal Doppler spectrum, and estimating the noise energy in the signal by utilizing the short-time echo signal Doppler spectrum; estimating a clutter autocorrelation matrix by utilizing a target approach distance unit; establishing a Fourier-based dictionary matrix, and solving the l1 norm optimization problem to obtain a super-resolution Doppler spectrum of a target; extracting characteristics of the super-resolution Doppler spectrum of the target; and classifying the extracted characteristics by using a classifier. By the method, the resolution ratio of the Doppler spectrum of the target is improved, the signal structure can be kept during adaptive clutter reduction, and the noise in the signal is suppressed; and moreover, the classification performance is improved, the noise robustness is obtained, and the method can be used for classifying moving vehicle targets with maneuvering parts.

The invention relates to a noise suppression method based on an inhomogeneous space solid array distributed SAR (Specific Absorption Rate), belonging to a noise suppression method and solving the problem that the traditional STAP (Space-Time Adaptive Processing) method is only suitable for noise suppression of a homogeneous linear array or homogeneous area array but not suitable for noise suppression of an inhomogeneous space array. The method comprises the steps of: firstly, establishing an inhomogeneous space solid array manifold; secondly, carrying out signal reconfiguration on the inhomogeneous space solid array manifold to obtain a homogeneous space solid array manifold; thirdly, computing and obtaining various dimensions of Doppler frequencies of noises according to the homogeneous space solid array manifold to obtain a noise model based on the homogeneous space solid array manifold; and fourthly, constructing full time space self-adaptive filter according to the noise model, various dimensions of Doppler frequencies and a full time space self-adaptive processing method. The invention overcomes the defects of the prior art, and can be used for noise suppression field in the SAR ground moving target detection technology.

A target is detected under a forest canopy or other elevated clutter where the target is obscured by the elevated clutter. Radar returns reflected from the target on the surface, combined with those from the elevated clutter are digitized. Motion compensation is performed for the radar returns with respect to the target to obtain a focused first synthetic aperture image of the target. Next, the radar returns are motion compensated with respect to the elevated clutter at various heights above the surface to obtain images of the elevated clutter. The elevated clutter within the images at the various heights above the surface is identified and coherently subtracted from the original synthetic aperture images.

A target is detected under a forest canopy or other elevated clutter where the target is obscured by the elevated clutter. Radar returns reflected from the target on the surface, combined with those from the elevated clutter are digitized. Motion compensation is performed for the radar returns with respect to the target to obtain a focused first synthetic aperture image of the target. Next, the radar returns are motion compensated with respect to the elevated clutter at various heights above the surface to obtain images of the elevated clutter. The elevated clutter within the images at the various heights above the surface is identified and coherently subtracted from the original synthetic aperture images.

The invention discloses a clutter suppression method based on knowledge-assisted sparse iterative covariance estimation, and solves the problem of poor clutter suppression performance of the conventional space-time adaptive processing technology because of non-uniformity of the clutter environment. The implementation steps are listed as follows: computing an airborne radar space-time steering vector matrix; determining an initial clutter power matrix and constructing an intermediate variable; computing a clutter power matrix in iteration by means of the intermediate variable; performing iteration to obtain the final clutter power matrix; determining a space-time covariance matrix constructed by the data of one unit to be detected and the corresponding weight; and traversing all the units to be detected so as to obtain the space-time adaptive processing result. The clutter covariance matrix is reconstructed by using the data of the units to be detected so as to avoid non-uniformity of the training samples, effectively suppress high ground clutters and improve the detection performance of the slow moving target; and the computational burden is low, the real-time performance is betterand engineering implementation is easy so that the clutter suppression method is suitable for the airborne radar to suppress the high ground clutters in the non-uniform environment and detect the slow ground moving target.

A radar receiver on a moving platform images a moving target and non-moving clutter using a single SAR array. The radar receiver converts the radar returns into digital radar returns and motion compensates the digital radar returns with respect to a reference, then applies further phase compensation to obtain an autofocused synthetic aperture image. A plurality of moving target pixels descriptive of the moving target are detected within the autofocused synthetic aperture image. The plurality of moving target pixels are transformed from the autofocused image to the time domain. The time domain moving target data is focused by iteratively applying a phase compensation to the time domain moving target data.

The invention discloses a device and a method for predicting a ground target motion trail of an unmanned aerial vehicle. A moving target data acquisition module acquires data of a ground moving target through an onboard sensor system in an onboard device of the unmanned aerial vehicle. A moving target data processing module converts a ground moving target motion trail three-dimensional polar coordinate into a three-dimensional rectangular coordinate, performs standardization processing on target trail data and the performs analytical prediction. A moving target trail generating module invokes a ground moving target trail predicting method in a predicting method library, performs analytical prediction on trail standardization data of the moving target and generates a prediction result. A moving target trail recommendation module calculates the recommendation level of the current moving target trail prediction result according to the standardization data and the prediction result. The device and the method for predicting the ground target motion trail of the unmanned aerial vehicle have the advantages of being capable of effectively predicting the ground target motion trail and providing reliable information for an unmanned aerial vehicle mission planning system and the like.

The invention belongs to the technical field of aircraft radar clutter and interference rejection, and particularly relates to an aircraft radar ground moving target detection method under an intensive forwarding type interference environment. The aircraft radar ground moving target detection method under the intensive forwarding type interference environment comprises the following steps that a receiving array of an aircraft radar receives corresponding return signals in the corresponding direction, corresponding constant false-alarm detection is conducted in a Doppler channel range corresponding to a Doppler distinct area according to the return signals received in each direction of the aircraft radar, and corresponding constant false-alarm detection results are obtained; according to the constant false-alarm detection results, wave arriving directions of forwarded interference signals are obtained; then airspace guide vectors of the forwarded interference signals are obtained; according to the airspace guide vectors of the forwarded interference signals, the maximum likelihood estimation value of the ground moving target signal amplitude is obtained; a ground moving target is detected according to the maximum likelihood estimation value of the ground moving target signal amplitude.

The invention discloses a precise strike-oriented ground moving target detection and recognition method. The method comprises the steps of: combining space-time information to extract a target candidate region, wherein the time-domain information is utilized to acquire moving images, forward-moving history graphs and backward-moving history graphs are calculated according to the moving images, images obtained by carrying out minimum-value acquisition on the forward-moving history graphs and the backward-moving history graphs according to pixels are used as input images, candidate moving regions are obtained through self-adaptive threshold processing and communication-domain extraction, the space-domain information is utilized to calculate materiality scores of the candidate moving regions , and the target candidate region is obtained through threshold processing; and recognizing the target candidate region, wherein feature learning is completed through local low constraint encoding, a linear support vector machine is utilized to realize recognition for the target candidate region, and a candidate region recognized as specific targets is reserved to obtain a final detection result. The method realizes automatic detection and recognition for the multiple ground moving targets in a complex environment, and improves the strike precision.

The invention discloses an unmanned aerial vehicle to ground moving target detection method based on vision. The method includes: utilizing feature extraction and matching to estimate interframe moving parameters; utilizing a color distribution and comparison mode to remove a 'ghost image' during movement detection; removing interference of trees by building a plant model; creating a mode mutex classifier, and classifying moving targets like 'buildings / moving targets' and 'vehicles / pedestrians' to further remove parallax interference of buildings so as to realize realtime unmanned aerial vehicle to ground moving target detection. The method does not relate to large-scale numerical value calculation and can meet needs on calculating complexity of small unmanned aerial vehicle to ground moving target detection.

The invention provides a method for realizing the characteristic extraction of a ground moving target micro-tremor signal based on a sparse decomposition theory, and problems of the long running time of a sparse decomposition algorithm, many occupied resources, a long process of searching a most matched atom, and the insufficient characteristic extraction and a high dimensional decomposition parameter of a signal caused by noise interference in an actual environment can be solved. The concrete method comprises the following steps: (1) establishing an over-complete atom dictionary corresponding to a target signal, taking the scale, the displacement, the frequency, the amplitude and the projection value of an atom as change parameters and carrying out parameter discretization, setting the change range of the parameters according to the characteristics of the target signal and the prior knowledge, and carrying out normalization on the atom to obtain a characteristic atom library corresponding to the micro-tremor signal; (2) combining an optimized genetic algorithm (GA) with MP sparse decomposition, searching an atom with sparse parameter in an efficient and adaptive way, and obtaining a series of atomic parameters which describe signal characteristics; and (3) carrying out PCA principal component analysis to carry out vector dimensionality reduction on the obtained atom and extracting an effective component to be a final characteristic. By applying the method, the amount of calculation of a sparse decomposition algorithm can be effectively reduced, the algorithm speed and resource consumption are raised, and the characteristic can be effectively applied to the later target identification.

A radar receiver on a moving platform images a moving target and non-moving clutter using a single SAR array. The radar receiver converts the radar returns into digital radar returns and motion compensates the digital radar returns with respect to a reference, then applies further phase compensation to obtain an autofocused synthetic aperture image. A plurality of moving target pixels descriptive of the moving target are detected within the autofocused synthetic aperture image. The plurality of moving target pixels are transformed from the autofocused image to the time domain. The time domain moving target data is focused by iteratively applying a phase compensation to the time domain moving target data.

The invention provides a ground moving target track reconstruction method suitable for CSAR imaging. The method includes steps of S1, performing range compression on received CSAR moving target echo wave signals, dividing full aperture echo waves of a radar into a plurality of sub aperture echo waves, converting the sub aperture echo waves into a distance Doppler domain, realizing moving target detection through Doppler filtering and constant false alarm rate detection and acquiring a position of the moving target in an RD domain; S2, realizing moving target correlation in different sub apertures by utilizing a multi-target tracking algorithm and acquiring the movement path of the moving target in the RD domain; S3, projecting the moving target RD domain track into a road grid and realizing moving target track reconstruction by utilizing a dynamic planning algorithm. According to the invention, a CSAR mode is adopted and long-term moving target observation capability is achieved. at the same time, through increasing road prior information and utilizing dynamic planning for solving an optimization equation, target track reconstruction precision can be improved.

The invention belongs to the field of synthetic aperture radar (SAR) ground moving target indication, and relates to a curve SAR (CSAR) ground moving target refocusing imaging method. The method comprises the following steps: S1, receiving a radar echo signal of a moving target, and preprocessing the radar echo signal; S2, dividing the radar echo signal into a plurality of sub-aperture echo signals along the azimuth direction; S3, transforming the sub-aperture echo signals into a distance frequency domain, and extracting phases of the signals along the azimuth direction one frequency point after another; S4, calculating a distance estimated value according to the extracted phases, and constructing a phase compensation factor by quadratic curve fitting; S5, performing motion compensation bythe phase compensation factor; S6, compensating for a phase estimation error by a map-drift (MD) self-focusing method; S7, performing Fourier transform along the azimuth direction and performing inverse Fourier transform along the distance direction respectively to obtain a moving target re-focusing result under a current sub-aperture; and S8, repeating the steps S3 to S7 to obtain a moving target re-focusing image sequence under a plurality of sub-apertures. Through adoption of the method, motion compensation is realized under the situation that target motion parameters are unknown.

The invention discloses a multichannel SARGMTI image domain two-step processing method. The method comprises the following steps of performing time delay compensation and channel equalization processing on echo signals subjected to distance pulse compression by taking a reference channel as a benchmark; sequentially carrying out azimuth spectrum compression and dechirping processing on the registered signals, and transferring data to a two-dimensional image domain; performing combined clutter suppression processing on each channel image outside the reference channel and the reference channel image in the two-dimensional image domain to obtain a clutter suppression result; performing constant false alarm detection on each clutter suppression result to obtain a moving target detection result; returning to the image domain before clutter suppression according to the moving target detection result, extracting the joint pixel data of each moving target one by one to perform local joint optimal processing for spectrum estimation, and estimating the radial speed of the moving target; and marking each moving target in the reference channel image, and performing repositioning processing onthe moving targets. According to the invention, high-probability detection and high-precision speed measurement and positioning of a ground moving target can be realized while a static scene is imaged.

The invention discloses a squint SAR ground moving target extracting method. The squint SAR ground moving target extracting method comprises the following steps that 1, echo signals of a stationary target and a moving target are computed; 2, range direction Fourier transformation is carried out; 3, consistent range walk correction is carried out on a range frequency domain and an orientation time domain; 4, range direction residual phase compensation is carried out; 5, variable parameter extension azimuth nonlinear CS is carried out; 6 the echo signals subjected to the extension azimuth nonlinear CS are multiplied by corresponding azimuth minus factors respectively and are transformed to the azimuth frequency domain; 7, the amplitudes of the two echoes are subtracted, the echo of the stationary target is removed, and stationary target clutter suppression is achieved; 8, amplitude detection and moving target extraction are carried out. The method solves the problems that the range and azimuth are coupled seriously in a ground moving target under the single-channel squint mode and moving target movement parameters are unknown, estimation of movement parameters is not needed, efficiency is higher, and the method can be widely used in the fields of clutter suppression, moving target extraction and the like.

The invention belongs to the technical field of radar, and discloses an SAR ground moving target imaging method based on sub-aperture parameter estimation. The method comprises the following steps: dividing original echo data into sub-aperture echo data and establishing a full-aperture instantaneous pitch model and a sub-aperture distance frequency domain echo data model on the basis of assumptions of target maneuvering motion in a full-aperture CPI and uniform motion of a target in a sub-aperture CPI; estimating parameters of the sub-aperture echo data; calculating a full-aperture instantaneous Doppler frequency vector by using the echo data parameters; obtaining a full-aperture instantaneous Doppler frequency vector model by using the full-aperture instantaneous pitch model; substitutingthe instantaneous Doppler frequency vector into the instantaneous Doppler frequency vector model; solving a coefficient to be determined, and correcting a high-order phase error of the full-apertureoriginal echo data by using the coefficient to be determined, thereby greatly improving the focusing level of a moving target under a large squint SAR imaging mode and obtaining images with better quality.

The invention discloses a ground target classification method based on a random forest and data rejection, which comprises the following steps: (1) preprocessing a training sample set; (2) extractinga training feature matrix; (3) training a random forest classifier; (4) preprocessing the test sample; (5) extracting test feature vector; (6) calculating the output probability vector of the ground target; (7), judging whether that t sample is rejected or not; (8) if the judgment is rejected, taking the test sample as the echo signal without the fretting characteristic of the target; (9) if the judgment is not rejected, outputting the corresponding class of the maximum value in the probability vector as the ground target classification result of the test sample. The method rejects the judgment of clutter, deceptive interference and non-fretting target signal, improves the classification and recognition rate of ground moving target, and adopts a classifier with parallel processing abilityto improve the real-time performance of the method.