Airborne Radar System Research Articles

УДОСКОНАЛЕНИЙ МЕТОД МАТЕМАТИЧНОГО МОДЕЛЮВАННЯ ФУНКЦІОНУВАННЯ БОРТОВИХ РАДІОЛОКАЦІЙНИХ СТАНЦІЙ УПРАВЛІННЯ ЗБРОЄЮ В УМОВАХ АКТИВНОЇ ПРОТИДІЇ СТАНЦІЯМ ПЕРЕШКОД ПРОТИВНИКА

The article describes an improved method for mathematical modeling of the functioning of the onboard radar in conditions of active opposition to the jammers of the enemy. The analysis of modern airborne radar systems and stations of active hindrances as objects of mathematical modeling, and existing methods of active resistance to the on-Board jammers of the enemy and methods of mathematical modeling of the functioning of the onboard radar. Generated input data for the modeling of the performance of airborne radars in noisy environments and active opposition to the jammers of the enemy, given a selected situation of air combat, which is subject to mathematical description. Were the selected indicators and criteria, characterizing efficiency of functioning of the onboard radar, the main of which is the restriction on the range of their use, depending on the applied method of resistance. Preliminary calculations regarding the application of these methods is active opposition. Given the peculiarities of application of active methods of combating enemy jamming stations, it is proposed to divide the cycle of air combat between aircraft on 5 stages, depending on the distance between them. The algorithm justify the selection of methods of countering enemy jamming stations taking into account the distance between the aircraft for continuous tracking and determined the probability of target tracking with the use of different combinations of ways of counteraction. For proper and complete evaluation of the performance of airborne radars is proposed to use fuzzy sets and the theory of games, by means of what a mathematical model of evaluating the performance of airborne radars in the conditions of active opposition to the jammers of the enemy, which was used during development of the algorithm and selecting the most efficient combination of ways to counter.

Robust Two-Stage Reduced-Dimension Sparsity-Aware STAP for Airborne Radar With Coprime Arrays

Space-time adaptive processing (STAP) algorithms with coprime arrays can provide good clutter suppression potential with low cost in airborne radar systems as compared with their uniform linear arrays counterparts. However, the performance of these algorithms is limited by the training samples support in practical applications. To address this issue, a robust two-stage reduced-dimension (RD) sparsity-aware STAP algorithm is proposed in this work. In the first stage, an RD virtual snapshot is constructed using all spatial channels but only $m$ adjacent Doppler channels around the target Doppler frequency to reduce the slow-time dimension of the signal. In the second stage, an RD sparse measurement modeling is formulated based on the constructed RD virtual snapshot, where the sparsity of clutter and the prior knowledge of the clutter ridge are exploited to formulate an RD overcomplete dictionary. Moreover, an orthogonal matching pursuit (OMP)-like method is proposed to recover the clutter subspace. In order to set the stopping parameter of the OMP-like method, a robust clutter rank estimation approach is developed. Compared with recently developed sparsity-aware STAP algorithms, the size of the proposed sparse representation dictionary is much smaller, resulting in low complexity. Simulation results show that the proposed algorithm is robust to prior knowledge errors and can provide good clutter suppression performance in low sample support.

Interference Environment Model Recognition for Robust Adaptive Detection

The recognition of the interference environment for adaptive radar detection is addressed in this article. Typically, detectors are designed in one specific scenario which may not be appropriate for the varying interference environment, especially for the airborne and space-based radar system. In this article, the considered recognition task is cast in terms of multiple hypothesis tests and the theory of model order selection (MOS) techniques are exploited to devise suitable decision rules. The interference environments are divided into homogeneity, partial homogeneity, and spherically invariant random process. Three MOS techniques, namely, the Akaike information criterion (AIC), generalized information criterion, and corrected AIC, are adopted. At the analysis stage, illustrating examples for the influence of the environment model parameters on the recognition accuracy of the MOS rules are presented. Numerical experiments show the AIC rule has the most robust recognition performance.

Dimension‐reduced bi‐iterative space–time adaptive processing method for airborne radar

A novel bi-iterative dimension-reduced space–time adaptive processing (STAP) algorithm for clutter suppression and moving target detection in airborne radar system is proposed. A dimension-reduced processing in both space and time is firstly performed. Then a bi-quadratic cost function is constructed to estimate the dimension-reduced spatiotemporal filter coefficients, which are used for suppressing the clutter and keeping the target signal. An optimal solution to the cost function can be obtained efficiently by a bi-iteration algorithm. Theoretical analysis and computer simulation results illustrate that the algorithm has fast convergence, low computation load and sampling requirements. The results of experiment by using the measured data show the validity of the proposed algorithm.

Track‐before‐detect algorithm for airborne radar system

This study considers the detection of dim target via track-before-detect (TBD) in airborne radar system. Dim target detection by TBD is well-studied while aircraft ego-motion is not taken into account. Ego-motion of the aircraft (platform) causes traditional TBD method useless in airborne radar system by two reasons. On one hand, the movement of the aircraft causes measurement misaligned among different frames. On the other hand, state space and measurement space is non-one-to-one correspondence. Considering these two issues, the authors proposed a TBD algorithm for airborne radar based on plots (AR-P-TBD). First, they derived coordinate rotation and motion compensation formula, and convert each frame of measurement into a unified coordinate system to make these measurements aligned. Then, TBD processing in measurement space is implemented. It avoids the non-one-to-one correspondence between state space and measurement space. Simulation results demonstrate the effectiveness of AR-P-TBD.

Grating-Lobe Clutter Suppression in Uniform Subarray for Airborne Radar STAP

This paper aims to address grating-lobe clutter suppression in a uniform subarray (US) for the airborne radar system. Due to the sparsity at the subarray level and different scanning angles between the inner subarray and the subarray, grating lobes are produced. The grating-lobe clutter then enters the main lobe, defined as main grating-lobe clutter (MGLC). When the target falls into the MGLC with the same Doppler frequency, the clutter cannot be effectively suppressed by the conventional space-time adaptive processing (STAP) algorithm. Hence, we design a transmit beamforming (TB)-STAP algorithm based on a modified phased array (MPA) radar system, where TB suppresses the MGLC, while STAP suppresses the main-lobe and sidelobe clutter; the goal is to maximize the output signal-to-clutter-plus-noise ratio (SCNR). The optimal solution of TB-STAP can be obtained through several iterations, and in each iterative algorithm, the TB is a quadratically constrained quadratic problem (QCQP) solved via the semidefinite relaxation (SDR) technique, and the STAP can obtain a closed solution by the minimum variance distortionless response (MVDR) algorithm. The simulation results show that compared with traditional STAP in PA and multiple-input multiple-output (MIMO) radars, the proposed algorithm in MPA radar greatly improves the output SCNR.

Block‐sparse representation of radar scattering centres for land‐based vehicles

The scattering centre model is well known as an approximation to provide a sparse abstraction of complex targets in radar applications. On the basis of the block-sparsity and high-frequency approximations, an improved scattering centre representation scheme is proposed for different angular observations of the land-based vehicles. For good insights into target physics and feature stability, the land-based vehicle is observed by airborne radar system in separate observation sections according to independent aspect angle regions. On the basis of that, the image patch of the land-based vehicle can be reconstructed with the measurements in each observation section. To reduce redundant information, compressive sensing followed by the CLEAN algorithm is exploited to extract the scattering centres from each image patch separately. Thus, the predominant scattering centres of the land-based vehicle can be grouped into several sub-structures with respect to the image patches. Numerical simulations are used to verify the validity and efficiency of the block-sparse representation (SR) scheme. The block-sparse representation scheme can be implemented with low computational complexity and flexibly extended to further research with multiple targets representation and applications in the radar field.

Exploiting persymmetry for JDL‐STAP

Joint domain localisation (JDL) is a popular reduced-dimension space-time adaptive processing (STAP) technique for clutter suppression in an air-borne radar system. Here, the authors develop an improved JDL method by exploiting persymmetric covariance matrix, referred to as persymmetric joint domain localisation (Per-JDL), in order to make maximum use of training samples and further improve the STAP performance under small training data support. The proposed algorithm is verified to be efficient in training-limited scenarios by simulation results.

DDMA MIMO radar system for low, slow, and small target detection

The low, slow, and small (LSS) target detection has always been a problem for both ground-based and air-borne radar systems. The factors such as weak target reflection energy, ground clutter, and random Doppler component will have a severe impact on radar detection performance. In recent years, researches on multiple-input multiple-output (MIMO) radar system have achieved great progress. By utilising multi-channel and multi-waveform technology, MIMO radar can form equivalent phase centres and virtual apertures to provide more system freedom and enhance detection performance. To address the LSS target-detection problem, the authors propose a novel Doppler division multiple access (DDMA) MIMO radar system, which employ DDMA waveform to ensure the orthogonality of the transmit signal and avoid some of the problems in the application of frequency division multiple access (FDMA) and code division multiple access (CDMA) for the actual radar system. The sparse array is employed to supress the grating lobe of the beam pattern and improve the angle estimation performance by optimising the position of the antenna array elements. Finally, the architecture of the designed radar system is introduced and the results of the detection performance to LSS targets based on real measured data is given.

Directional wave spectra at the regional scale with the KuROS airborne radar: comparisons with models

In situ observations, satellite observations, and regional observations from airborne remote sensing are very useful to characterize sea state evolution and related physical processes, improve numerical modeling, and contribute to climate variable survey. Directional wave spectra describe the complexity of sea state and give access to parameters such as directional parameters (mean direction and directional distribution of energy) and frequency parameters (peak frequency, frequency spread). In this paper, directional ocean wave spectra and their parameters, retrieved from observations carried out with the airborne radar system KuROS during two field campaigns, are analyzed. These campaigns provide a very rich variety of meteorological conditions: high wind conditions either fetch-limited cases or mature sea conditions and moderate wind conditions and sea state dominated by swell. The objective of this paper is to compare the KuROS data set with numerical wave model outputs and buoy observations. This comparison aims first at assessing the performances on main wave parameters (significant wave height, mean direction at the peak, peak frequency) retrieved from KuROS in different conditions (wind sea, swell, mixed seas), and then, to discuss on parameters characterizing the shape of the wave spectra, namely the frequency and the directional spread. Results of the comparisons show that, due to the size of the KuROS radar footprint, ocean waves with dominant wavelengths lower than 200 m are the most appropriate situations for wave retrieval. They also show an overestimation of the model frequency spread and an underestimation of the model directional spread compare to KuROS and buoy data for both campaigns.

Universal mathematical model of SAR signals for natural surfaces

The implementation of the basic version of the universal mathematical model of the formation of reflected signals for various airborne radar systems, including the synthetic antenna aperture radar, when working on natural surfaces are discussed in the article. A number of parameters are required to study, which must be taken into account for the correct modeling of echo signals, which must then be processed to calculate radar images. A method for constructing such a mathematical model in MATLAB is presented with some modeling results for a homogeneous rough surface and two typical pulse and continuous modulation signals. But the facet parameter structure of the simulated surface can take into account the possibilities of representing various types of terrain and objects created by man.

Industry insights: Post conference report: International conference on radar 2018

The International Conference on Radar was held in Brisbane, Queensland, Australia for the first time on August 27–30, 2018. With the theme New Frontiers in Radar, the conference attracted some 309 delegates from 27 countries. On the first day, seven tutorials drew 144 attendees, and covered topics including airborne radar systems, synthetic aperture radar, automotive radar systems, passive radar, target recognition, radar clutter, and phased arrays.

Design and research on a power distribution system for airborne radar

With the rapid progress of electronic and computer technology, as well as the application requirements under complicated conditions, modern airborne radars are developing to multifunction, highly integrated, digital and modular. As a ‘heart’ component of the radar, the performance and reliability of the distribution system is one of the decisive factors for its development. In this work, the design and research of an airborne radar power distribution system was introduced. The distribution system adopts the layered and fused power supply architecture of ‘centralized rectification, decentralized voltage stabilization’. Further, according to the actual application requirements, the input under-voltage and over-voltage protection, health management and other functional modules were added. The detailed composition, design and the corresponding implementation scheme of the distribution system were carefully investigated. The test results show that the system is controllable, stable and reliable, and the performance index meets the requirements of the radar system for the power supply characteristics. The distribution system is feasible, and has important reference significance for the design of power supply and distribution system of other radars.

LPI time‐based TMS against high‐sensitivity ESM

Low probability of interception (LPI) time refers to a time during which a certain airborne radar system is tracking the target without being intercepted by a high-sensitivity electronic support measurement (HSESM) on the target. LPI time is determined by the tracking process of the certain airborne radar system and the interception performance of an HSESM. This study proposes a track mission shifting (TMS) tactic of the distributed airborne radar system (DARS) or distributed airborne formation radar system (DAFRS) based on LPI time. First, this study defines a short-time average interception probability of HSESM on frequency search mode. Then, with adaptive dwell time design and the maximum illumination interval algorithm based on predicted tracking error covariance matrix, this study proposes to take interactive multiple models Kalman filter to describe target tracking process and introduces binary hypothesis test of chi-square and non-central chi-square distributions as target detection criterion during target tracking. Finally, with a partial prior knowledge of the opposed HSEMS on the target, this study proposes a TMS tactic model based on LPI time. Simulations show that LPI time is a significant reference value for DARS or DAFRS to turn over track mission against an opposed HSEMS.

Drone-borne ground-penetrating radar suitability for specific surveys: a comparative study of feature sizes versus antenna frequency and elevation over the ground

Abstract The applications of airborne ground-penetrating radar (GPR) antennas or systems are not as widespread and well-developed as their counterparts, the conventional ground coupled antennas and While GPR airborne systems are not a novelty at systems. This has led to a situation in which airborne systems are normally used in a niche industry with very strict guidelines and expectations, such as the road surveying industry (Saarenketo and Scullion, 2000). Airborne antennas are, regrettably, often operated in very inefficient ways, sometimes disregarding basic physical laws or plain, fundamental principles of GPR technology. When the antenna is lifted from the ground a whole new set of problems and complexities arise and, if not taken into consideration, they can lead to very unreliable data and wrong interpretation of the obtained results.

Detection and Imaging of Moving Targets With LiMIT SAR Data

Detecting moving targets in synthetic aperture radar (SAR) imagery has recently gained a lot of interest as a way to augment optical moving target detection and classification in adverse (e.g., cloudy) weather conditions. In this paper, we primarily focus on the problem of detecting and imaging moving targets in single-channel (or summed multichannel) SAR data. Single-channel-based methods provide the ability to do detection well below the normal minimum detectable velocity (MDV) of multichannel-based GMTI. This can be particularly important for small radar antennas, which tend to have high conventional GMTI MDV. We also show results for multiple channel geolocation after single-channel detection and imaging. The algorithms consist of the following steps. We first suppress the stationary scene by comparing noncoherent time-subimages. We then detect the movers by applying a set of possible motion corrections to the image and use a novel matched filter to detect the movers in this space. We can then image the moving targets using standard SAR focusing techniques and geolocate the movers using multichannel (if available) along-track interferometry. We demonstrate and evaluate our algorithms using data collected from the Lincoln Multimission ISR Testbed airborne radar system.

Accuracy and Probabilistic Characteristics of the Helicopter Flight Mode Recognition Algorithm in an Airborne Radar System

Accuracy and Probabilistic Characteristics of the Helicopter Flight Mode Recognition Algorithm in an Airborne Radar System

Knowledge-Aided Covariance Matrix Estimation via Kronecker Product Expansions for Airborne STAP

This letter proposes a new approach for knowledge-aided estimation of structured clutter covariance matrices (CCMs) in airborne radar systems with limited training data. First, we model the CCM in space–time adaptive processing (STAP) as a sum of low-rank Kronecker products. We then apply a permutation operation to convert the Kronecker factors into linear structures and propose a novel CCM estimation method under the maximum-likelihood framework. Employing a proximal gradient algorithm, the proposed method simultaneously exploits the knowledge about the clutter and the Kronecker structure of the CCM. We finally evaluate the performance of the proposed method using real data from airborne STAP.

An Improving EFA for Clutter Suppression by Using the Persymmetric Covariance Matrix Estimation

The extended factored approach (EFA) is believed to be one of the most efficient and practical space–time adaptive processing (STAP) algorithms for clutter suppression in an airborne radar system. However, it cannot effectively work in the airborne radar system with large antenna array for the huge computational cost and the lack of training sample. To solve these problems, a bi-iterative algorithm based on the persymmetric covariance matrix estimation is proposed in this paper. Firstly, the clutter covariance matrix is estimated by using the original data, the constructed spatial transformed data, the constructed temporal transformed data and the constructed spatial–temporal transformed data. Secondly, the spatial weight vector in EFA is decomposed as the Kronecker products of two short weight vectors. Finally, the bi-iterative algorithm is exploited to obtain the desired weight vectors. Thus, the improving EFA with small training sample demanding is realized. Experimental results demonstrate the effectiveness of the proposed method under small training sample support.

Slow-moving Target Detection Method for Airborne MIMO Radar Using Doppler Frequency Movable Waveform

For an airborne radar system, the detection of moving target under the ground clutter has become the research hotspot to worldwide scholars. And the detection of the slow-moving target near the main clutter area is now regarded as one of the difficulty problem. In order to reduce the Minimum Detectable Velocity (MDV) of moving target, a novel slow-moving target detection method is presented for airborne MIMO radar, which transmits Doppler frequency movable waveform (DFMW). By combining the advantages of the MIMO radar and the DFMW, the proposed method could realize the suppression of ground clutter and the detection of the slow-moving target near main clutter area effectively. Simulation results confirm the effectiveness of the proposed method.