To detect small infrared targets under the condition of dense clutters, we propose a single-frame target detection algorithm based on a small bounding-box filter, which is characterized by good adaptability to the position and size of a small target. During the small target detection process, the proposed algorithm first searches for the local maximum gray pixel and then, a set of concentric bounding boxes whose center is the pixel found in the first step is constructed, and the detection thresholds of a neighboring region of this pixel are calculated based on the bounding boxes. Finally, the minimum threshold is used to detect small target pixels in the neighboring region. A fast version of the proposed algorithm is a minimum bounding-box filter, which can be implemented by dividing an image into blocks and using the mid-range and range to assess the concentration trend and dispersion of the background. Simulation and analysis results show that the proposed algorithm can achieve high detection probability and low false alarm rate when detecting small targets in the complex background; while its fast version has high computational efficiency. The proposed algorithm can be used in infrared searching and tracking systems.
KEYWORDS: Target detection, Detection and tracking algorithms, 3D acquisition, Hough transforms, Signal to noise ratio, Data storage, Binary data, Optical engineering, Computer simulations, 3D image processing
We propose a 3D Hough transform (3D-HT) algorithm that can overcome the disadvantages of high complexity and large data storage space of the existing 3D-HT-based small target detection algorithms. The proposed algorithm uses two coordinates at different times and coordinate errors to construct a 3D pipeline. Subsequently, it counts the number of points in the 3D pipeline and confirms the presence of a target trajectory in the pipeline when the number of points exceeds a predefined threshold. Finally, it performs trajectory merging and filtering before outputting the target trajectory coordinates. The proposed algorithm has low complexity because the used trajectory parameters are the coordinates in the data space, and only a linear transform between the coordinates is required. Unlike the existing algorithms that use an accumulator array to represent the Hough space, the proposed algorithm uses only a single position-adaptive cumulative cell in the Hough space. Therefore, there is no limitation on data storage in the Hough space. Simulation and analysis show that the small target detection algorithm based on the proposed transform is robust to noise, requires small data storage space, and has high computational efficiency. The proposed algorithm can be used in infrared and radar small target trajectory detection systems.
This paper introduces the basic principle of the INS/CNS integrated navigation system, and introduces and compares the working modes and combination modes of various INS/CNS integrated navigation systems. Then it points out the key technologies of INS/CNS integrated navigation system. The application of integrated navigation in airborne platforms, missile–borne platforms, spaceborne platforms, shipboard platforms, and other platforms is summarized. Finally, the development direction of INS/CNS integrated navigation is analyzed. This article reviews the INS/CNS integrated navigation technology and provides a reference for scientific researchers in the field of navigation.
A resolution improved monochromator based on tunable Fabry-Perot (F-P) filter and grating hybrid modulator was presented. The light was firstly filtered by the tunable F-P filter and then diffracted by the grating. The tunable F-P filter was used to achieve multi-orders narrow linewidth monochromatic light spectrally and the grating was in charge of separating the multi-orders monochromatic light spatially. By adjusting the rotation angle and the cavity length of the hybrid modulator, the wide spectral range can be achieved. A visible hybrid modulator was designed and the simulation results demonstrated the resolution of a monochromator system was improved in the spectral range of 400~800nm.
We propose tunable Fabry-Perot filters constituted by double high contrast gratings (HCGs) arrays with different periods acting as reflectors separated by a fixed short cavity, based on high reflectivity and the variety reflection phase shift of HCG array which realize dynamic regulation of the filtering condition. Single optimized HCG obtains the reflectivity of higher than 99% in a grating period ranging from 0.68μm to 0.8μm across a bandwidth of 30nm near the 1.55μm wavelength. The filters can achieve the full width at half maximum (FWHM) of spectral line of less than 0.15nm, and the linear relationship of peak wavelengths and grating periods is established. The simulation results indicate a potential new approach to design a tunable narrowband transmission filter.
Autonomous celestial navigation based on stellar refraction has attracted widespread attention for its high accuracy and full autonomy.In this navigation method, establishment of accurate stellar refraction measurement model is the fundament and key issue to achieve high accuracy navigation. However, the existing measurement models are limited due to the uncertainty of atmospheric parameters. Temperature, pressure and other factors which affect the stellar refraction within the height of earth's stratosphere are researched, and the varying model of atmosphere with altitude is derived on the basis of standard atmospheric data. Furthermore, a novel measurement model of stellar refraction in a continuous range of altitudes from 20 km to 50 km is produced by modifying the fixed altitude (25 km) measurement model, and equation of state with the orbit perturbations is established, then a simulation is performed using the improved Extended Kalman Filter. The results show that the new model improves the navigation accuracy, which has a certain practical application value.
A reliable and secure navigation system and assured autonomous capability of satellite are in high demand in case of emergencies in space. This paper introduces a novel autonomous orbit determination method for Middle-Earth-Orbit and Low-Earth-Orbit (MEO and LEO) satellite by observing space objects whose orbits are known. Generally, the geodetic satellites, such as LAGEOS and ETALONS, can be selected as the space objects here. The precision CCD camera on tracking gimbal can make a series of photos of the objects and surrounding stars when MEO and LEO satellite encounters the space objects. Then the information processor processes images and attains sightings and angular observations of space objects. Several clusters of such angular observations are incorporated into a batch least squares filter to obtain an orbit determination solution. This paper describes basic principle and builds integrated mathematical model. The accuracy of this method is analyzed by means of computer simulation. Then a simulant experiment system is built, and the experimental results demonstrate the feasibility and effectiveness of this method. The experimental results show that this method can attain the accuracy of 150 meters with angular observations of 1 arcsecond system error.
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