Moving Ground Objects Research Articles

Estimation of tangential speed of ground moving targets in SAR

In parallel with the development of systems of highly detailed mapping of the underlying surface, methods of ground moving targets indication (GMTI) were also improved. A dramatic improvement in the resolution characteristics of onboard radars occurred after the introduction of mapping modes with synthetic artificial antenna aperture. The advent of synthetic aperture radars (SAR) made it possible to detect ground moving targets (GMT) against the background of reflections from the underlying surface, which made it possible to further implement GMTI algorithms for detecting low-speed moving ground objects. The simple way to carry out GMTI is if the observed target has a radial component of the velocity vector, which generates a Doppler frequency shift in the reflected signal. A more complex situation arises when it is necessary to detect targets moving at a tangential speed relative to the onboard radar. The difficulty of detecting targets moving at tangential speed is due to the fact that target movement in the direction perpendicular to the line of sight leads to deformation of the phase structure of the signal. This particular deformation manifests itself in the appearance of quadratic phase modulation of the reflected trajectory signal. With consistent signal processing in mapping mode, due to the appearance of quadratic phase modulation, the response of the observed moving target will be defocused. To detect the presence of a moving target with tangential speed, it is proposed to use an algorithm similar to the well-known phase difference algorithm for autofocusing radar images. It consists in dividing the implementation of the trajectory signal into two parts, after which the bottom of them is subjected to a complex conjugation procedure. Next, the two implementations are multiplied with each other and the amplitude spectrum of the result of the multiplication is calculated. The shift of the maximum spectral density relative to the origin is proportional to the tangential velocity of the observed target. The sign of the shift (to the right or to the left) depends on the direction of movement of the GMT relative to the velocity vector of the carrier. This algorithm was justified by an analytical method, then its mathematical modeling was carried out. In the case of observation of spruce trees by on-board radar with a high tangential velocity, the error in its estimation increases, which is due to the spreading of the spectrum of the signal reflected from the GMT to reduce the influence of this effect.

Coordinated Vision-Based Tracking by Multiple Unmanned Vehicles

We address the problem of coordinated vision-based tracking of a moving target using multiple unmanned vehicles that exchange information over a supporting time-varying network. The objective of this work is to formulate decentralized control algorithms that enable multiple vehicles to follow the target while coordinating their phase separation. A typical scenario involves multiple unmanned aerial vehicles that are required to monitor a moving ground object (target tracking) while maintaining a desired inter-vehicle separation (coordination). To solve the vision-based tracking problem, the yaw rate of each vehicle is used as the control input, while the speeds of the vehicles are adjusted to achieve coordination. It is assumed that the vehicles are equipped with an internal autopilot, which is able to track yaw rate and speed commands. The performance of the coordinated vision-based tracking algorithm is evaluated as a function of the target’s velocity, tracking performance of the onboard autopilot, and the quality of service of the communication network.

Standoff tracking of a ground target based on coordinated turning guidance law

Target tracking is a typical application of unmanned aerial vehicles(UAVs). However, it is difficult for the existing guidance laws to meet the requirements of convergence speed and tracking accuracy at the same time. A new guidance law based on a coordinated turning equation is proposed to achieve target tracking, and its asymptotic stability is proved. Linear analysis is provided to help select the control parameters. This guidance law is improved to track the moving ground object with time-varying states. Compared with existing methods through numerical simulations, the proposed guidance law offers a faster convergence speed and a higher level of precision. The effectiveness and robustness of the guidance law in different situations are verified by hardware-in-the-loop (HIL) simulations.

ИССЛЕДОВАНИЕ КОМПЛЕКСНЫХ АДАПТИВНЫХ АЛГОРИТМОВ ОБРАБОТКИ ИНФОРМАЦИИ ДЛЯ НАВИГАЦИОННЫХ СИСТЕМ ПОДВИЖНЫХ НАЗЕМНЫХ ОБЪЕКТОВ

ИССЛЕДОВАНИЕ КОМПЛЕКСНЫХ АДАПТИВНЫХ АЛГОРИТМОВ ОБРАБОТКИ ИНФОРМАЦИИ ДЛЯ НАВИГАЦИОННЫХ СИСТЕМ ПОДВИЖНЫХ НАЗЕМНЫХ ОБЪЕКТОВ

Протидія радіолокаційним засобам виявлення наземних об'єктів

Розглянуто питання маскування малорозмірних рухомих наземних об'єктів від сучасних засобів виявлення і розвідки. Наведено рекомендації щодо захисту малорозмірного наземного об'єкта від радіометричних пасивно-активних систем виявлення. Проведено пошук радіопо-глинальних матеріалів для створення маскувальних покриттів типу «Накидка» і «Терновник» на території України.

Coordinated Target Tracking via a Hybrid Optimization Approach.

Recent advances in computer science and electronics have greatly expanded the capabilities of unmanned aerial vehicles (UAV) in both defense and civil applications, such as moving ground object tracking. Due to the uncertainties of the application environments and objects’ motion, it is difficult to maintain the tracked object always within the sensor coverage area by using a single UAV. Hence, it is necessary to deploy a group of UAVs to improve the robustness of the tracking. This paper investigates the problem of tracking ground moving objects with a group of UAVs using gimbaled sensors under flight dynamic and collision-free constraints. The optimal cooperative tracking path planning problem is solved using an evolutionary optimization technique based on the framework of chemical reaction optimization (CRO). The efficiency of the proposed method was demonstrated through a series of comparative simulations. The results show that the cooperative tracking paths determined by the newly developed method allows for longer sensor coverage time under flight dynamic restrictions and safety conditions.

Unmanned aerial vehicles cooperative path planning for ground target tracking via chemical reaction optimization

Recent advance in computer science and electronics has greatly expanded the capabilities of unmanned aerial vehicles (UAV) in both military and civil applications, such as moving ground object tracking. Due to the uncertainties of the application environments and objects motion, it is difficult to maintain the tracked object always within the sensor coverage area by using a single UAV. Hence, it is necessary to deploy a group of UAVs to improve the robustness of the tracking. In this paper, we investigate the problem of tracking ground moving object from a group of UAVs using body-fixed sensors under flight dynamical and collision-free constraints. The optimal cooperative tracking path planning problem is solved using an evolutionary optimization technique based on the framework of chemical reaction optimization (CRO). The efficiency of the proposed was demonstrated through a series of comparative simulations. Experimental results show that the cooperative flyable paths determined by the new method allow for longer sensor coverage time under flight dynamical and safety conditions.

Automatic Extraction of Traffic Flows Using TerraSAR-X Along-Track Interferometry

Spaceborne synthetic aperture radar (SAR) offers great potential for the measurement of ground traffic flows. A SAR with multiple receiving apertures aligned in flight direction repeatedly images the same ground area with a short time lag. This allows for an effective detection of moving ground objects, whose range variation translates into an interferometric phase signal between the receiving channels. The high-resolution German SAR satellite TerraSAR-X offers several ways to create multiple along-track apertures. We exploit this to demonstrate satellite-based traffic-flow measurements using along-track interferometry (ATI) and Displaced Phase Center Array techniques. In this paper, we address the usage of different TerraSAR-X ATI modes for data acquisition and describe an automatic near-real-time processing chain for the extraction of traffic information. The performance of this TerraSAR-X traffic processor is significantly driven by incorporating <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> knowledge of road networks. We present examples of automatic traffic detection as well as empirical evaluations thereof using different kind of reference data.

Radar determination of moving ground objects in the millimeter wavelength range

The problem of radar determination of moving surface targets in the millimeter wavelength range has been studied using the analysis in the frequency-time domain of the short-term power spectrum of nonstationary signal. A procedure was proposed for generating the informative attributes on the basis of separate processing of the envelope and phase of signal reflected from a surface object. In addition, the presented results of experimental studies corroborated the efficiency of the identification algorithm discussed.

A Vision System for Intelligent Mission Profiles of Micro Air Vehicles

Recently, much progress has been made toward the development of small-scale aircraft, known broadly as Micro Air Vehicles (MAVs). Until recently, these platforms were exclusively remotely piloted, with no autonomous or intelligent capabilities, due at least in part to stringent payload restrictions that limit onboard sensors. However, the one sensor that is critical to most conceivable MAV missions, such as remote surveillance, is an onboard video camera and transmitter that streams flight video to a nearby ground station. Exploitation of this key sensor is, therefore, desirable, since no additional onboard hardware (and weight) is required. As such, in this paper we develop a general and unified computer vision framework for MAVs that not only addresses basic flight stability and control, but enables more intelligent missions as well. This paper is organized as follows. We first develop a real-time feature extraction method called multiscale linear discriminant analysis (MLDA), which explicitly incorporates color into its feature representation, while implicitly encoding texture through a dynamic multiscale representation of image details. We demonstrate key advantages of MLDA over other possible multiscale approaches (e.g., wavelets), especially in dealing with transient video noise. Next, we show that MLDA provides a natural framework for performing real-time horizon detection. We report horizon-detection results for a range of images differing in lighting and scenery and quantify performance as a function of image noise. Furthermore, we show how horizon detection naturally leads to closed-loop flight stabilization. Then, we motivate the use of tree-structured belief networks (TSBNs) with MLDA features for sky/ground segmentation. This type of segmentation augments basic horizon detection and enables certain MAV missions where prior assumptions about the flight vehicle's orientation are not possible. Again, we report segmentation results for a range of images and quantify robustness to image noise. Finally, we demonstrate the seamless extension of this framework, through the idea of visual contexts, for the detection of artificial objects and/or structures and illustrate several examples of such additional segmentation. This extension thus enables mission profiles that require, for example, following a specific road or the tracking of moving ground objects. Throughout, our approach and algorithms are heavily influenced by real-time constraints and robustness to transient video noise.