Infrared Search And Track Systems Research Articles

AESA radar and IRST against low observable threats

PurposeModern fighter aircraft using active electronically scanned array (AESA) fire control radars are able to detect and track targets at long ranges, in the order of 50 nautical miles or more. Low observable or stealth technology has contested the radar capabilities, reducing detection/tracking ranges roughly to one-third (or even less, for fighter aircraft radar). Hence, infrared search and track (IRST) systems have been reconsidered as an alternative to the radar. This study aims to explore and compare the capabilities and limitations of these two technologies, AESA radars and IRST systems, as well as their synergy through sensor fusion.Design/methodology/approachThe AESA radar range is calculated with the help of the radar equation under certain assumptions, taking into account heat dissipation requirements, using the F-16 fighter as a case study. Concerning the IRST sensor, a new model is proposed for the estimation of the detection range, based on the emitted infrared radiation caused by aerodynamic heating.FindingsThe maximum detection range provided by an AESA radar could be restricted because of the increased waste heat which is produced and the relevant constraints concerning the cooling capacity of the carrying aircraft. On the other hand, IRST systems exhibit certain advantages over radars against low observable threats. IRST could be combined with a datalink with the help of data fusion, offering weapons-quality track.Originality/valueAn original approach is provided for the IRST detection range estimation. The AESA/IRST comparison offers valuable insight, while it allows for more efficient planning, at the military acquisition phase, as well as at the tactical level.

Dim and small infrared target fast detection guided by visual saliency

In order to detect dim and small infrared targets from a mass of high-resolution images of omni-directional Infrared Search and Track (IRST) systems rapidly and accurately, a fast target detection method guided by visual saliency (TDGS) is proposed. In this method, a coarse-to-fine detection strategy is used. First, in the stage of coarse-detection, according to the differences of global features between targets and backgrounds, a global saliency model based on fast spectral scale space (FSSS) is constructed to suppress complex background regions rapidly. And visual salient regions which contain dim and small targets are extracted from the original image. Then, in the stage of fine-detection, according to differences of local contrast between targets and background, an adaptive local contrast method (ALCM) is applied to finely improve contrast of targets in visual salient regions. Candidate targets can be further extracted through the adaptive threshold segmentation. Finally, dim and small targets are detected by their temporal relativity in multi-frames. Experimental results on four typical image sequences have indicated that the proposed method can not only detect dim and small infrared targets with small amount of computation, high detection probability, and low false alarm rate, but also adapt to various complex backgrounds. It is suitable for dim and small targets detection in omni-directional IRST systems and other practical applications.

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.

Optimum selection of detection point and threshold noise ratio of airborne infrared search and track systems.

To improve the recognition probability of airborne infrared search and track systems (IRSTS) in air-to-air operations, the point target recognition probability model is established. And using an operating range model, the detection envelope is calculated for the airborne IRSTS. Combining with different operational backgrounds and specific technical parameters, the simulation results show that: (1)an increase in visual range and target speed, along with a decrease of oblique angle, produces an increase in the recognition probability; (2)the angle of maximum operating range of each detection envelope is the optimum detection point for the airborne IRSTS; and (3)the optimum threshold noise ratio is 8-10. These conclusions provide further scope in improving the operational effectiveness of airborne IRSTS in practical applications.

Fusion Detection Algorithm for Infrared Dim Target based on Temporal-Spatial Domain Accumulation and Difference

Aiming at the problem of the dim target real-time detection in Infrared search and track (IRST) systems, a fusion detection algorithm for infrared dim target based on temporal-spatial domain accumulation and difference is proposed. The proposed algorithm suppresses background and enhances targets by template filtering and difference processing in space domain, and the image sequences are processed by multiframe energy accumulation and frame difference methods according to the target’s moving characteristics in time domain. After the fusion segmentation of the temporal and spatial processing results with definite rule, the target can be detected by the relation of the possible target’s position in adjoining frames according to target’s moving continuity and regularity. Experimental results show that the proposed algorithm enormously increases the target's SNR after the temporal-spatial fusion enhancement, and it has high detection probability and high detecting speed. In the meantime, the algorithm is easy to realize in hardware and can be applied effectively in the real-time target detection of the IRST systems.

New Approach in Processing of the Infrared Image Sequence for Moving Dim Point Targets Detection

The development of an efficient moving target detection algorithm in IR-image sequence is considered one of the most critical research fields in modern IRST (Infrared Search and Track) systems, especially when dealing with moving dim point targets. In this paper we propose a new approach in processing of the Infrared image sequence for moving dim point targets detection built on the transformation of the IR-image sequence into 4-vectors for each frame in the sequence. The results of testing the proposed approach on a set of frames having a simple single pixel target performing a different motion patterns show the validity of the approach for detecting the motion, with simplicity in calculation and low time consumption.

Detection performance loss due to jitter in naval IRST systems

Infrared search and track (IRST) systems based on 3-D velocity filters are quite sensitive to the random motion that remains after egomotion compensation has occurred (jitter). These systems are designed to detect small targets at long range and they often employ track-before-detect (TBD) strategies to integrate the target signal along consecutive frames. Jitter causes frame misalignment and leads to a reduction of the detection performance. We analyze the effects of jitter on the false alarm and detection probabilities and on the detection range. The analytical expressions here derived are a valuable tool both in the analysis and synthesis of IRST systems based on 3-D velocity filters.

English

Infrared search and track (IRST) systems are required for fighter aircraft to enable them to passively search, detect, track, classify, and prioritise multiple airborne targets under all aspects, look-up, look-down, and co-altitude conditions and engage them at as long ranges as possible. While the IRST systems have been proven in performance for ground-based and naval-based platforms, it is still facing some technical problems for airborne applications. These problems arise from uncertainty in target signature, atmospheric effects, background clutter (especially dense and varying clouds), signal and data processing algorithms to detect potential targets at long ranges and some hardware limitations such as large memory requirement to store and process wide field of view data. In this paper, an overview of airborne IRST as a system has been presented with detailed comparative simulation results of different detectionitracking algorithms and the present status of airborne IRSTs