Infrared Search And Track System Research Articles

Analysis and Design of Infrared Search and Track System with Afocal Zoom Telescope

The infrared search and track system (IRST) is a type of special electrical optical (EO) system that can be used in various scenarios to fulfill situation awareness, reconnaissance, and tracking of targets. We proposed a homogeneous coordinate transformation method to analyze the residual image wandering induced by the rotation of the scanning platform and the compensation fast steering mirror and help with the commonly trivial selection of the telescope magnification and the objective focal length. The analysis and simulation are carried out with specified IRST optics, which adopt a 640 × 512 array and 15 μm pitch detector, in a focal range of 60 mm~360 mm, and a scan speed of 360°/s to 60 °/s at 50 fps, and optical specifications are determined further. The presented optical system, with only three kinds of common infrared materials, works at 3.7 μm~4.8 μm, demonstrates good image performance and tolerance characteristics, and shows potential in manufacturing. Also, the resulting image wandering of 8 μm, less than a 0.6-pixel size, at an integral time of 16 ms, proves the correctness of the method and makes the scheme of considerable interest for electrical optical systems.

An Enhanced Image Patch Tensor Decomposition for Infrared Small Target Detection

Infrared small-target detection is a key technology for the infrared search and track system (IRST), but some problems still exist, such as false detections in complex backgrounds and clutter. To solve these problems, a novel image patch tensor (IPT) model for infrared small-target detection is proposed. First, to better estimate the background component, we utilize the Laplace operator to approximate the background tensor rank. Secondly, we combined local gradient features and highlighted area indicators to model the local targets prior, which can effectively suppress the complex background clutter. The proposed model was solved by the alternating direction method of multipliers (ADMM). The experimental results on various scenes show that our model achieves an excellent performance in suppressing strong edge clutter and estimating small targets.

Refining Atmosphere Profiles for Aerial Target Detection Models.

Atmospheric path radiance in the infrared is an extremely important quantity in calculating system performance in certain infrared detection systems. For infrared search and track (IRST) system performance calculations, the path radiance competes with the target for precious detector well electrons. In addition, the radiance differential between the target and the path radiance defines the signal level that must be detected. Long-range, high-performance, offensive IRST system design depends on accurate path radiance predictions. In addition, in new applications such as drone detection where a dim unresolved target is embedded into a path radiance background, sensor design and performance are highly dependent on atmospheric path radiance. Being able to predict the performance of these systems under particular weather conditions and locations has long been an important topic. MODTRAN has been a critical tool in the analysis of systems and prediction of electro-optical system performance. The authors have used MODTRAN over many years for an average system performance using the typical “pull-down” conditions in the software. This article considers the level of refinement required for a custom MODTRAN atmosphere profile to satisfactorily model an infrared camera’s performance for a specific geographic location, date, and time. The average difference between a measured sky brightness temperature and a MODTRAN predicted value is less than 0.5 °C with sufficient atmosphere profile updates. The agreement between experimental results and MODTRAN predictions indicates the effectiveness of including updated atmospheric composition, radiosonde, and air quality data from readily available Internet sources to generate custom atmosphere profiles.

Small infrared target detection using absolute average difference weighted by cumulative directional derivatives

Infrared search and track (IRST) systems have attracted more attention in recent years due to advances of infrared imaging technology. In a typical IRST system, small infrared detection algorithm is the most challenging part of the system development procedure. In this paper, an effective algorithm based on the average absolute gray difference (AAGD) is presented. In the first step, the main deficiencies of the AAGD algorithm are investigated precisely. After identifying three major drawbacks of the AAGD algorithm, a powerful small target detection algorithm is developed through compensating every single weak-spot in the AAGD algorithm. The simulation results on real infrared images prove that the proposed algorithm not only compensates the AAGD disadvantages but also outperforms the recently published well-known small infrared target detection algorithms in both qualitative and quantitative perspectives.

Relative navigation for autonomous aerial refueling rendezvous phase

A relative navigation system for autonomous aerial refueling (AAR) rendezvous phase is proposed in this paper. The system uses the inertial navigation system (INS), the Global Positioning System (GPS) and the infrared search and track system (IRST). It has both advantages of cooperative aircraft relative navigation and passive target location. A hybrid multistage fusion structure and corresponding algorithm are designed to estimate the high precision relative position, velocity and attitude information between the tanker and the UAV in real time. For the INS/GPS subsystem, a two-stage filtering algorithm based on extended Kalman filter is developed without any use of base-station, which helps to improve the accuracy of the filter model. Considering the requirement of reliability and robustness for aerial refueling, an independent IRST relative state tracker filter is set up in the system. It weakens the dependence of relative navigation system on data link, and makes the system highly reliable and fault-tolerant. The numerical simulation results indicate that the proposed algorithm can provide good performance in terms of accuracy and reliability.

Staring array infrared search and track performance with dither and stare step

Operationally significant infrared search and track (IRST) systems have been primarily second-generation thermal imager technology with scanned time-delay-integration (TDI) detector operation. The benefit of the scanned technology provides for large aperture, gimbal-scanned sensors with extremely wide field of regard, but with low revisit rates. Dramatic progress in large format staring arrays has provided the possibility of higher performance systems with lower complexity. These large format infrared staring arrays may be able to provide systems with higher performance (due to detector count) with less complexity (fewer gimbal scan limitations). In fact, lower performance IRST systems may satisfy operational requirements without scanning or stare-step operation in a “strap-down” architecture. The first step in a full capability staring system IRST design requires a thorough knowledge of staring array IRST performance. This knowledge includes a basic understanding of signal to noise (SNR) in both undersampled and well-sampled systems, with and without a matched filter. For undersampled systems, unresolved targets result in low SNR in both the average case and worst-case scenarios. We assess (using SNR as our primary metric) how the staring IRST system benefits from typical staring operations, such as dither and stare step. We provide a comparison of staring IRST system performance in the midwave infrared (MWIR) and longwave infrared (LWIR) with three modes of operation: basic staring (no sensor movement), dither, and stare step. In addition, we introduce a metric that allows comparison of different types of IRST systems. We use this metric to compare the performance of MWIR and LWIR as well as staring, dither, and stare-step systems. In the future, we will compare scanned systems to staring IRST systems.

A false-alarm aware methodology to develop robust and efficient multi-scale infrared small target detection algorithm

False alarm rate and detection rate are still two contradictory metrics for infrared small target detection in an infrared search and track system (IRST), despite the development of new detection algorithms. In certain circumstances, not detecting true targets is more tolerable than detecting false items as true targets. Hence, considering background clutter and detector noise as the sources of the false alarm in an IRST system, in this paper, a false alarm aware methodology is presented to reduce false alarm rate while the detection rate remains undegraded. To this end, advantages and disadvantages of each detection algorithm are investigated and the sources of the false alarms are determined. Two target detection algorithms having independent false alarm sources are chosen in a way that the disadvantages of the one algorithm can be compensated by the advantages of the other one. In this work, multi-scale average absolute gray difference (AAGD) and Laplacian of point spread function (LoPSF) are utilized as the cornerstones of the desired algorithm of the proposed methodology. After presenting a conceptual model for the desired algorithm, it is implemented through the most straightforward mechanism. The desired algorithm effectively suppresses background clutter and eliminates detector noise. Also, since the input images are processed through just four different scales, the desired algorithm has good capability for real-time implementation. Simulation results in term of signal to clutter ratio and background suppression factor on real and simulated images prove the effectiveness and the performance of the proposed methodology. Since the desired algorithm was developed based on independent false alarm sources, our proposed methodology is expandable to any pair of detection algorithms which have different false alarm sources.

English

In current warfare scenario stealth and passive threat detection capabilities are considered as prime requirements to accomplish desired mission by the fighter aircrafts. To improve the stealth of an aircraft, the trend is towards detecting threats with the help of passive sensors (Electro Optic or Infrared). Current situation caters for systems like Infra-red Search and Track (IRST) and Passive Missile Warning Systems (PMWS). IRST system is a passive target detection system, used for detecting aerial & ground targets. PMWS is a threat detection system used for detecting missiles approaching towards aircraft. Both of these systems detect targets of interest by processing IR images acquired in mid-IR region. The prime challenge in IRST system or PMWS is detecting a moving target of size typically 1~2 pixels in acquired image sequences. The temporal change caused by moving target in consecutive frames can be considered as one important factor to detect them. The temporal change caused by moving target is identified through absolute frame differencing of successive frames. This principle has limitation in application to IRST & PMWS as the imaging sensor with the aircraft is moving. This motion also imparts temporal change in the acquired images. In this paper authors are proposing a method for removing the temporal change caused by the platform motion in two consequently acquired frames using registration process. The proposed method uses the platform attitude information at frame sampling times. Authors have analyzed the sensitivity of registration process to noisy platform attitude information. Defence Science Journal, 2014, 64(2), pp. 130-135. DOI: http://dx.doi.org/10.14429/dsj.64.5460

밝기 차, 유사성, 근접성을 이용한 적응적 표적 검출 알고리즘

적외선 탐색 및 추적 시스템에서 원거리에 표적이 존재할 경우 표적의 크기가 매우 작고, 해무와 같은 클러터와 다양한 센서 잡음으로 인해 표적의 검출이 매우 어렵다. 특히 표적의 화소 값과 유사한 잡음이나 클러터가 존재하는 경우 일반적인 임계화 기법을 적용하는 경우 표적의 오검출 위험이 매우 높다. 이러한 이유로 본 논문에서는 영상의 밝기 정보와 표적에 대한 사전 정보를 이용하여 최적의 표적 검출 결과를 도출하기 위한 적응적 임계화 기법을 제안한다. 소형 표적을 강조하기 위하여 인간 시각 시스템을 반영한 CSF(Contrast Sensitivity Function)를 적용하고, 표적이 강조된 영상에서 영상의 밝기 정보와 거리 정보를 이용하여 표적을 검출한다. 다양한 환경 조건에서 획득된 적외선 영상에 대한 실험 결과들은 제안 알고리즘의 견실한 성능을 보여준다. In IRST(infrared search and track) system, the small target detection is very difficult because the IR(infrared) image have various clutter and sensor noise. The noise and clutter similar to the target intensity value produce many false alarms. In this paper. We propose the adaptive detection method which obtains optimal target detection using the image intensity information and the prior information of target. In order to enhance the target, we apply the human visual system. we determine the adaptive threshold value using image intensity and distance measure in target enhancement image. The experimental results indicate that the proposed method can efficiently extract target region in various IR images.

형태학적 연산에 기반한 해수면 온도 분포 추정 알고리즘

원거리의 표적을 탐지하기 위한 IRST시스템에서 표적은 배경영역에 포함된 많은 클러터로 인하여 검출이 매우 어렵다. 특히 해상 환경에서 획득된 영상의 경우, 불균일한 해수면 온도 분포는 원거리에서 접근하는 소형 표적의 검출을 어렵게 하는 요인으로 작용한다. 이에 본 논문에서는 형태학적 연산을 기반으로 하는 불균일한 해수면 온도 분포를 추정하는 알고리즘을 제안한다. 정확한 해수면 온도 분포 추정을 위하여 상한 분포와 하한 분포로 나누어 추정하고, 추정된 결과의 평균값으로 최종 해수면 온도 분포를 도출한다. 또한 형태학적 연산을 적용함으로써 발생하는 서브샘플링 효과 문제를 해결하기 위하여 다양한 크기의 구조요소를 이용하는 다중 가중치(multi-weight) 기법을 적용한다. 제안 방법의 타당성을 검증하기 위하여 다양한 환경에서 획득된 해수면 영상에 대한 해수면 온도 분포 추정 결과를 기존 알고리즘과 비교 검증하였다. Target detection is very difficult with complex clutters in IRST(Infrared Search and Track) system for a long distance target. Especially sea-clutter and ocean-surface with non-uniform temperature distribution make it difficult to detect incoming targets in images obtained in sea environment. In this paper, we propose a novel method based on morphological method for estimation of ocean surface with non-uniform temperature flow. In order to estimate the exact ocean surface temperature flow, we divided it into upper and lower bound flow. And after estimating it, the final ocean surface temperature flow is derived by a mean value of the estimated results. Also, we apply the multi-weighted technique with a variety of sizes of structure elements to overcome sub-sampling effect by using morphology method. Experimental results for ocean surface images acquired from many different environments are compared with results of existing method to verify the performance of the proposed methods.

Detection algorithm of targets for infrared search system based on area infrared focal plane array under complicated background

Infrared Search and Track (IRST) system is a wide field of view surveillance system, meant for autonomous search, detection, acquisition, and cue of potential targets. The first and second generation IRSTs utilized detectors with multiple elements followed by discrete preamplifiers for signal read-out. They have many performance limitations. With the advent of infrared focal plane array (IRFPA) sensors, the present trend is to build IRSTs based on line FPA sensors to achieve higher sensitivity and resolution. This article describes a new IRST system, different from other systems with area infrared focal plane array (IRFPA), using area infrared focal plane array (AFPA). This system has the simple and reliable structure. First this paper described the surveillance system based on AFPA. And the Point Scattering Function (PSF) of degradation model images blurred by AFPAs’ rotations and the imaging feature of the targets is presented. And the target detection algorithm is described and analyzed, the maximum filter and center filter is advanced. Finally the experiment results have proved that the IRST system using AFPA has high detection ratio and low false alarm ratio.

Bearings-Only Target Motion Analysis Using a Dual-Waveband Infrared System

Infrared systems are widely used for target detection, designation and tracking. For example, an Infrared Search and Track (IRST) system, as a typical airborne or shipboard detecting device, is widely equipped for the remote target detection and tracking. In recent years, the problem of target motion analysis (TMA) and tracking has been studied increasingly extensively. In an airborne infrared system, the problem becomes more difficult due to absence of range information. In this paper, the infrared model and motion model of typical aerial targets are described. An airborne dual-waveband IRST system, which is quite familiar nowadays, is choosed for implementation of target motion analysis. Based on the above, a novel and more practical algorithm of target tracking via bearings-only measurements is formed and the major parameters are defined according to a typical airborne dual-waveband IRST system. Finally, data simulation is implemented, and the results demonstrate the new algorithm has a better performance than before for bearings-only target tracking.