Detection Of Airborne Targets Research Articles

Research on the Application of Multi-Source Radar Signal Fusion Technology in Airborne Target Detection

Research on the Application of Multi-Source Radar Signal Fusion Technology in Airborne Target Detection

Low-contrast scene feature-based infrared nonuniformity correction method for airborne target detection

The fixed mode noise (FPN) caused by the nonuniform response of the infrared focal plane array (IRFPA) will inevitably affect the image quality, so the nonuniformity correction (NUC) method is needed to eliminate such noise. Most of the traditional NUC methods are suitable for high-contrast scenes but do not work as well in low-contrast scenes such as sky and water. Therefore, this paper proposes an infrared NUC method based on feature extraction and image registration for low-contrast scenes and combines the Kalman filter to accelerate the convergence speed, which achieves a good NUC effect. A threshold gating mechanism of learning rate is proposed to eliminate the influence of discrete defective pixels without losing the details of the target. In simulation, the proposed method can achieve high-precision image registration in low-contrast scenes, and the registration error can be less than 0.5 pixels under the condition of a signal-to-noise ratio (SNR) of 3. The experimental results of real infrared images show that the average roughness index of 0.0563 and the target SNR of 7.99 can be obtained after correcting the real infrared image with the proposed method, both of which are better than other methods, thus verifying the effectiveness and superiority of the proposed method.

Multi-channel track-before-detect approach for airborne target with OTH radar

It is a common requirement for over-the-horizon (OTH) radar to detect the sea and airborne targets in the same direction simultaneously. The long coherent integration time (CIT) is needed to detect the sea target and the weak moving target such as aircraft. However, the range walk effect (RWE) will occur within the long integration time, leading to a serious degradation of the airborne target detection and tracking. To settle this problem, a new approach based on the multi-channel track-before-detect (MC-TBD) is proposed in this paper. More specifically, to improve the detection performance of the airborne target with unknown speed, multiple processing channels corresponding to different speed ranges are set under the MC-TBD framework. The received data are processed in each channel in parallel. In each channel, the constraints of the speed range are utilized to determine the number of pulses in the CIT of the airborne target. Then, coherent and noncoherent integration processing are performed sequentially based on the moving target detection (MTD) and track-before-detect (TBD). Finally, the detection results and trajectories of all channels are fused to achieve the final detection and tracking of the airborne target. Simulation results show the superiority of the proposed MC-TBD approach over the existing methods in terms of the performance of detection and tracking for airborne target with OTH radar under the background of simultaneous detection of airborne and sea targets in the same direction.

Airborne Infrared Imaging Simulation for Target Recognition

Aiming at the needs of airborne infrared target recognition in various fields, this paper proposes a holistic infrared vision simulation framework. We present a full-link infrared imaging model of the target and background in the 3D scene, through the research on the mechanism of infrared imaging, and the infrared target recognition model is designed in the information processing module to realize the infrared detection of airborne targets. Finally, the whole simulation framework is implemented and verified in this paper. By combining parallel simulation and deep learning technology, the development and application of infrared target recognition will be further promoted.

Detection of small targets in the infrared: an infrared search and track tutorial.

Airborne target detection in the infrared has been classically known as infrared search and track or IRST. From a military point of view, it can be described as target detection at long ranges where the target image is subpixel in size. Here, the target is "unresolved." It can also describe the detection of aircraft near the observer using distributed apertures in a spherical detection field. From a commercial point of view, an important application is drone detection near live airport operations. As drones become more common, the dual-use functionality of IRST systems is expanding. Technology improvements for IRST systems include the wide proliferation of infrared staring focal planes. New readout integrated circuits allow for time-delay-integration of large format detectors. Stare-step sensors in the future appear to be as common as gimbal-scanned thermal imagers. Detection probability analysis and IRST sensor design is different than targeting system design. We provide a tutorial here on IRST system calculations as well as discussions on broadband versus spectral calculations and new technology considerations.

Using information processing algorithms that factor in the effect of secondary modulation of radar signals

The article provides an assessment of the impact the dynamic structures of power systems of aircraft systems have on the spectrum of the reflected radar signal. In the conditions of autonomous actions of the fighter, the tasks of long-range detection of airborne targets are assigned directly to the onboard radar station. It is necessary to resolve the contradictions associated with increasing the detection range without changing the energy indicators of the onboard radar station. This is possible by optimizing the processing of many spectral components of the signal reflected from the propeller and turboprop engine of airborne targets. The location of propeller reflections in the spectrum of the reflected signal is determined by the technical parameters of the power plant and its mode of operation. The percent of the total energy of the reflected signal spectrum outside the main spectral component is comparable with the energy reflected from the airframe of the aviation complex, most of which is the energy reflected from the rotating elements of power plants. Therefore, the development of an algorithm for detecting a signal with a complex spectral structure that maximizes the probability of detection under time and computational resources restrictions is a very relevant scientific task. The scientific novelty lies in the development of an algorithm for detecting a signal with a complex spectral structure and its detection characteristics taking the effect of secondary modulation into account as well as in the development of practical recommendations for optimizing algorithms for detecting airborne targets. Using the developed algorithm in the fighter’s pulse-Doppler radar station will increase the detection range of an air target against the background of interfering reflections from the water surface.

A Modified Sequential Multiplexed Method for Detecting Airborne and Sea Targets With Over-the-Horizon Radar

Phased array over-the-horizon (OTH) radar usually needs to detect sea target and airborne target in different directions. Conventionally, the sea target and airborne target are detected sequentially with the coherent integration completely accomplished for each of them. However, the long coherent integration time (CIT) required by the sea target makes the time interval between two airborne target detections too long, which is not conducive to tracking airborne target. To overcome this problem, this paper proposes a new timeframe multiplexing scheme, in which several short-time detections of airborne target are inserted into a long CIT of sea target detection. The proposed scheme seeks to improve the detection frequency of airborne target while ensuring the detection performance of two types of target. However, due to the insertion of airborne target detection, the echo from sea surface is received discontinuously which means that the coherent integration of sea target is incomplete. To tackle it, a recovery algorithm based on the Hankel structured matrix is introduced, which recovers the slow-time domain signal of each range bin and thereby guarantees the detection performance of sea target not damaged. Numerical simulations prove the effectiveness of the proposed algorithm for signal recovery, and also verify that the proposed operating scheme has a shorter time interval for airborne target detection, while the detection performance of two targets are well guaranteed.

An integrated gas-liquid droplet microfluidic platform for digital sampling and detection of airborne targets

The use of microfluidic droplets has become ubiquitous in many Lab-on-a-Chip (LOC) applications ranging from material synthesis to novel biochemical sensing. In this paper, we introduce a new droplet-based approach that incorporates a gas phase for generating liquid droplet microreactors in a microfluidic flow-focusing format. We demonstrate the subsequent on-chip transition, collection and handling of the droplets in a secondary liquid carrier inside a multilayer PDMS structure. The presented technique has potential applications in capturing and probing airborne particles and gaseous vapors using high surface-to-volume picoliter droplets. The discrete microfluidic gas-liquid interfaces created in this approach, greatly facilitate absorption and up-concentration of a gaseous target analyte into the droplet volume. The chip-based format of the units also allows for different microfluidic modules and analytical techniques to be integrated in this platform for droplet probing, providing highly-sensitive LOC detection systems. Here, we demonstrate the basic principles of sample partitioning with gas-liquid droplets by capturing and detection of vaporized ammonia at different gaseous concentrations using Nessler’s reaction inside the droplets. The results of this work provide a simple and robust quantification approach for determining gaseous ammonia which can be further expanded to other gas-phase analytes in next generation of airborne target detectors for human breath analysis and environmental monitoring.

Flying target detection and recognition by feature fusion

We present a near-real-time visual-processing approach for automatic airborne target detection and classification. Detection is based on fast and robust background modeling and shape extraction, while recognition of target classes is based on shape and texture-fused querying on a-priori built real datasets. The presented approach can be used in defense and surveillance scenarios where passive detection capabilities are preferred (or required) over a secured area or protected zone.

A Track Scoring Function Development for Airborne Target Detection Using Dynamic Programming

Track-before-detect techniques based on dynamic programming have provided solutions for detecting targets from a sequence of images. In its application to airborne threat detection, dynamic programming solutions should take into account the distinguishable properties of objects in a collision course. This paper describes the development of a new track scoring function that accumulates scores for airborne targets in Bayesian framework. Numerical results show that the proposed scoring function has slightly better detection capabilities.

Detection of airborne targets by space-based radar based on range migration correction

Detection of airborne targets by space-based radar based on range migration correction

Airborne threat detection in navy IRST systems

A new algorithm is presented for the detection of airborne targets by means of infrared sensors operating in naval surveillance scenarios. The proposed algorithm consists of two steps: background clutter removal and detection over the residual clutter. The algorithm is fully automatic and its implementation does not require the tuning of any parameter other than the threshold for setting the probability of false alarm. The algorithm performance is investigated by means of a sequence of experimental IR images taken in a typical maritime environment. The results show that the proposed algorithm outperforms a standard detection algorithm specifically tailored to the analysed scenario. A statistical analysis of the experimental data is also performed to validate the hypotheses used to derive the detection algorithm.

Passive millimeter wave imaging considerations for tactical aircraft

Air Force, Army, Navy, and NASA Research Laboratories, in addition to major aerospace companies, are considering millimeter wave (MMW) imaging technology as an enhancement to sensor suits on both occupied and unoccupied vehicles. This is a review of the basic technology involved in MMW imaging and some of the programs and products that might benefit from passive day or night imaging through mist, haze, fog, clouds, smoke and/or dust. Potential applications include UAV surveillance of ground vehicles, airborne approach to airfields, tankers, flight leaders, and detection of airborne targets, including stealth aircraft.

Space–time processing for the detection of airborne targets in IR image sequences

The problem of detecting airborne targets in a sequence of images recorded by a long range infra-red sensor is investigated. The generalised likelihood ratio test detector is derived. The detector structure and its actual implementation are discussed. Approximated expressions of the false alarm and detection probabilities are obtained and validated by means of simulations. Example results obtained on a set of experimental data are reported.

STAP for airborne target detection using a space-based phased-array radar

STAP for airborne target detection using a space-based phased-array radar

Ground and airborne target detection with bistatic adaptive space-based radar

We have demonstrated that by using adaptive space-time processing, it is possible to detect and locate slowly-moving targets immersed in strong ground clutter from a bistatic spaceborne radar.