Early Warning Radar Research Articles

Range-Ambiguous Clutter Suppression for Space-Based Early Warning Radar via EPC–FDA–MIMO With Nonorthogonal Waveforms

Range-Ambiguous Clutter Suppression for Space-Based Early Warning Radar via EPC–FDA–MIMO With Nonorthogonal Waveforms

A Novel Non-Stationary Clutter Suppression Approach for Space-Based Early Warning Radar Using an Interpulse Multi-Frequency Mode

The non-stationary clutter of space-based early warning radar (SBEWR) is more serious than that of airborne early warning radar. This phenomenon is primarily attributed to the Earth’s rotation and range ambiguity. The increase in clutter degrees of freedom (DOFs) and the significant widening of the clutter suppression notch are not conducive to moving target detection near main lobe clutter. This paper proposes an effective approach to suppress non-stationary clutter based on an interpulse multi-frequency mode for SBEWR. Using the orthogonality of the uniform stepping frequency signal, partial range ambiguity can be effectively suppressed, and the clutter DOFs will be reduced. Subsequently, joint pitch-azimuth-Doppler three-dimensional spacetime adaptive processing and slant range preprocessing are used to perform clutter suppression. This combination not only curtails the estimation error associated with the clutter covariance matrix but also enhances the overall detection capabilities of the system. The simulation results verify the effectiveness of the proposed approach.

Range-Ambiguous Clutter Suppression with Cascaded FDA-MIMO STAP for Bistatic Space-Based Early Warning Radar

Range-Ambiguous Clutter Suppression with Cascaded FDA-MIMO STAP for Bistatic Space-Based Early Warning Radar

A Novel Joint Dimensionality-Reduced Adaptive Clutter Suppression Method for Space-Based Early Warning Radar Utilizing Frequency Diversity Array

A Novel Joint Dimensionality-Reduced Adaptive Clutter Suppression Method for Space-Based Early Warning Radar Utilizing Frequency Diversity Array

Reduced-Dimension STAP Method via Beamforming Joint Subarray Synthesis for Space-Based Early Warning Radar

Reduced-Dimension STAP Method via Beamforming Joint Subarray Synthesis for Space-Based Early Warning Radar

Clutter Characteristic Analysis and Grating Lobe Suppression for Distributed Small Satellite Space-Based Early Warning Radar

Clutter Characteristic Analysis and Grating Lobe Suppression for Distributed Small Satellite Space-Based Early Warning Radar

A severely range ambiguous clutter suppression method based on multi‐domain cascaded signal processing for space‐based early warning radar

AbstractThe non‐stationary clutter phenomenon and the severe range ambiguity make space‐based early warning radar as an intricate model of received ground and sea clutter. The received clutter is severely broadened in Doppler dimension, and the degrees of freedom (DOFs) of the received clutter is severely increased. Because the DOFs of the system is always lower than the theoretical DOFs of the received clutter, the adaptive processing capability of the system is insufficient and the performance of clutter suppression is seriously degraded. A multi‐domain cascaded adaptive processing method is proposed in this study. The proposed method takes full advantage of the digital antenna array to suppress a portion of the clutter energy by introducing the transmit pulse coding domain, and the remaining influential clutter energy is suppressed by introducing the elevation‐dimensional receive channel domain. Finally, the clutter after the two‐dimensional (2D) pre‐processed is suppressed by the 2D adaptive processing in the azimuthal receive beam‐receive Doppler domain. This method pre‐processes the clutter data by extending the processing dimension to meet the freedom requirements of the adaptive signal processing, and the capability of clutter suppression is significantly improved. Simulation examples show the effectiveness of the proposed method.

Anti-Jamming Efficiency Evaluation of Field Air Defense Early Warning Radar

With the rapid development of radar, the role of enemy jammers in actual combat is becoming more and more prominent, and they play a very critical role in combat, jamming the "clairvoyance" (early warning radar) of our field air defense position, weakening the ability of our early warning radar to find targets, so it becomes very important to evaluate the anti-jamming effectiveness of early warning radar. In this paper, the effectiveness function is used to evaluate the jamming effectiveness of the early warning radar after the jamming. Finally, an example is given to verify the effectiveness of the evaluation method.

Range-Ambiguous Clutter Suppression for Space-Based Early Warning Radar Using Vertical FDA and Horizontal EPC

The range ambiguous clutter in space-based early warning radar is more severe compared with that in airborne radar due to the faster movement velocity. Meanwhile, the clutter angle-Doppler characteristics vary with range owing to Earth’s rotation. As a result, the mainbeam clutter returned from different ambiguous range occupies most of the Doppler spectrum, which leads to the degradation of the traditional space-time adaptive processing (STAP) performance in canceling clutter. Though frequency diverse array (FDA) based on multiple-input multiple-output can provide the ability to identify the range ambiguous clutter, it cannot perform well for space-based early warning radar because of the finite available vertical elements. In this paper, a novel STAP method, which utilizes the element-pulse coding (EPC) and FDA technique to mitigate the range ambiguous clutter, is proposed. Firstly, EPC is used to pre-whiten the most range ambiguous clutter via coding and decoding in horizontal elements and coherent pulses. Then the interval in the vertical frequency of the residual range-ambiguous clutter is expanded by FDA, and thus the targets and clutter from the vertical mainlobe are easily extracted using a spatial filter with a few vertical elements. Finally, the extracted clutter can be effectively suppressed through the traditional STAP method. Simulation results are provided to demonstrate the performance of the proposed method.

Research on Multi-Domain Dimensionality Reduction Joint Adaptive Processing Method for Range Ambiguous Clutter of FDA-Phase-MIMO Space-Based Early Warning Radar

The ground and sea clutter received by space-based early warning radar (SBEWR) has severely range ambiguous characteristics due to its platform location, and the non-stationary factor caused by Earth’s rotation makes the received clutter at different range ambiguous positions seriously broaden in the Doppler dimension. The complex clutter suppression performance of SBEWR obtained by traditional method is degraded significantly. To solve this problem and achieve better clutter suppression performance, a novel multi-domain adaptive processing method for clutter suppression is proposed in this paper. The proposed method introduced a range related signal processing domain based on conventional space–time domain by using frequency diverse array phase multiple-input multiple-output (FDA-Phase-MIMO) radar. In addition, a novel multi-domain joint dimensionality reduction structure was designed. The novel multi-domain joint adaptive processing using the proposed dimensionality reduction structure could not only obtain great clutter suppression performance of SBEWR, but also minimize the requirement of the number of selected auxiliary channels. Simulation examples show the effectiveness of the proposed method.

Improved Dimension-Reduced Structures of 3D-STAP on Nonstationary Clutter Suppression for Space-Based Early Warning Radar

By introducing degrees of freedom (DOFs) in elevation, the elevation-azimuth-Doppler three-dimensional space–time adaptive processing (3D-STAP) methods have better performance when suppressing the nonstationary clutter caused by the Earth’s rotation in space-based early warning radar (SBEWR). However, the 3D-STAP methods use much more auxiliary beams, leading to greater demands on the training samples and heavier computational burdens than the conventional STAP methods. To solve this problem, the ideas of sum–difference beams, generalized multiple beams and Doppler-domain localization are applied here, and three improved dimension-reduced structures of 3D-STAP are proposed in this article. After analyzing the characteristics and distribution of nonstationary clutter for SBEWR, we find that the demands for auxiliary beams are different in elevation, azimuth and Doppler dimension. In addition, the suggestion to choose the number of auxiliary beams in each dimension is given. Simulation experiments are conducted to verify the analysis and evaluate the performance of the proposed methods. The simulation results show that the proposed 3D-STAP methods have better performance and lower computational burdens than typical 3D-STAP methods.

Clutter Mitigation in Space-based Early Warning Radar Using a Convolutional Neural Network

Clutter Mitigation in Space-based Early Warning Radar Using a Convolutional Neural Network

An Anti-Main-Lobe Jamming Algorithm for Airborne Early Warning Radar based on APC-SVRGD Joint Optimization

Main lobe jamming seriously affects the detection performance of airborne early warning radar. The joint processing of polarization-space has become an effective way to suppress the main lobe jamming. To avoid the main beam distortion and wave crest migration caused by the main lobe jamming in adaptive beamforming, a joint optimization algorithm based on adaptive polarization canceller (APC) and stochastic variance reduction gradient descent (SVRGD) is proposed. First, the polarization plane array structure and receiving signal model based on primary and auxiliary array cancellation are established, and an APC iterative algorithm model is constructed to calculate the optimal weight vector of the auxiliary channel. Second, based on the stochastic gradient descent principle, the variance reduction method is introduced to modify the gradient through internal and external iteration to reduce the variance of the stochastic gradient estimation, the airspace optimal weight vector is calculated and the equivalent weight vector is introduced to measure the beamforming effect. Third, by setting up a planar polarization array simulation scene, the performance of the algorithm against the interference of the main lobe and the side lobe is analyzed, and the effectiveness of the algorithm is verified under the condition of short snapshot number and certain signal to interference plus noise ratio.

Forecasting technique of radio information system characteristics for optimal technical condition of the space control system components

The paper proposes a forecasting technique of radio information system characteristics for optimal technical condition of space control system components, using a recurrent neural network and information tools from an early-warning radar stations group and Russian Aerospace Forces optical-electronic stations when determining the optimal technical condition of the Space Monitoring System (SMS) components. Analyzing values of time series by a recurrent neural network LSTM-based model with various parameters, we propose an algorithm for solving problem of forecasting characteristics of a radio information complex. The network architecture is a two-layer network with one layer of LSTM cells and one fully connected layer. There are results of experimental forecasting by pre-training the recurrent neural network (RNN) model sampling 1080 normalized measurements of a conditional sensor of 30 minutes apart. The training sample is made of conditional sensor normalized values for 9 hours continuous operation. The algorithm for the model training and creation is implemented in Python language using open source library TensorFlow. Experiments were performed with different values of the forecast horizon and the length of the input sequence of time series values. We obtained: the total average error for each combination of parameters, the dependence of the average forecast error on the used parameters and the dependence of the average (for all forecast values) forecast error on the period of the analyzed sensor values.

A Novel Clutter Covariance Matrix Estimation Method Based on Feature Subspace for Space-Based Early Warning Radar

Accurate estimation of the clutter covariance matrix for the cell under test (CUT) is a committed step in the spatial-temporal adaptive processing (STAP) algorithm. The unique nonstationary characteristic of signal for space-based early warning radar (SBEWR) leads to the spatial variation of training sample and the insufficient number of optional independent identically distributed (i.i.d.) training samples, which brings difficulties to training sample selection and covariance matrix estimation. To improve the estimation accuracy of clutter covariance matrix and the performance of STAP for SBEWR in a heterogeneous environment, a novel training sample selection and clutter covariance matrix estimation method is proposed. The method based on clutter subspace reconstruction and spectrum correction technology can improve the estimation accuracy of clutter covariance matrix in the case of nonstationary signals and heterogeneous environments. The clutter covariance matrix estimated by the proposed method is similar to the clutter covariance matrix of the CUT, and the performance of STAP is improved. The experimental results confirm the performance of the proposed method.

Estimation of Solar Activity Based on VHF Radar Data

The index of integral solar activity F10.7 is one of the main input parameters of existing ionospheric models, including the model used at early-warning radar stations to compensate for coordinate information errors; the use of external sources of F10.7 seems to be impossible. A method is presented for highly reliable estimate of the solar X-ray flux values at a wavelength of 10.7 cm based only on the capabilities of the station itself.

Research on Optimization of Working Mode of Long-range Early Warning Radar Guided by Space-based Information

The long-range early warning radar is the key equipment in the early defense process of ballistic missile. For the problem of low working efficiency of long-range early warning radar without guidance information, this paper studies the working process of long-range early warning radar with space-based guidance information, and proposed a new long-range warning radar working mode. Firstly, the coordinate system transformation and guidance information extraction of space-based guidance information are given. Then the concept of coherent accumulation of radar signals is introduced and a new radar operation mode is proposed. Finally, the radar signal coherent accumulation process is established. A mathematical model of radar search distance and intercept probability. The typical scene is built and simulated. The results show that the proposed radar working mode will effectively reduce the search airspace of the long-range early warning radar and improve the radar detection range.

A Novel Waveform Design Method for Shift-Frequency Jamming Confirmation

Shift-frequency jamming is generally used to form range false targets for ground-based early-warning radar systems; the frequency shift value of such interference is larger than the Doppler shift value of the moving target, and the key element to suppress the shift-frequency jamming is the frequency shift value estimation. However, in the low- or medium-pulse repetition frequency (PRF) mode, it is challenging to estimate the accurate frequency shift due to the velocity ambiguity. To solve this problem, a novel sparse Doppler-sensitive waveform is designed based on the ambiguity function theory, where the basic idea is to design a waveform sensitive to a specific Doppler but insensitive to other Dopplers; therefore, this waveform can recognize the specific Doppler of the target unambiguously. To apply the designed waveform in practice, the detection and estimation processing flow is provided based on the waveform diversity technique and the family of the sparse Doppler-sensitive waveforms. Simulation experiments are presented to validate the efficiency of the proposed method, and we conclude that the advantage of this method is that it can be used to confirm the specific Doppler of the target unambiguously with few pulses even under the condition of a low PRF.

Operational Capability of Ship-to-Air Missile Weapon System

As operational capability of the weapon system can be varied with each fire, it proposes operational capability evaluation method for the weapon system, afterwards it proposes operational capability evaluation method for the weapon fire taking the impact indicators such as single target detection probability of shipborne early-warning radar into account.

Max van der Stoel and Latvia

Latvia was a very frequent stop in the busy travel schedule of Max van der Stoel during his tenure as the OSCE High Commissioner on National Minorities (HCNM) from 1993 to 2001. As the Director of the non-governmental Latvian Centre for Human Rights and Ethnic Studies from mid-1994 to the end of 2002, I met with the HCNM regularly over the years and had numerous telephone conversations with him and members of his staff to exchange information and coordinate strategy for pushing minority-related reforms. I came to have deep respect for his role in resolving some of the most sensitive political issues in post-independence Latvia. The political context in Latvia was extremely complicated in the early 1990s, and occasionally even dangerous. This required the utmost diplomatic skill from outside interlocutors, of which the HCNM was a key player. After regaining independence in August 1991 after 50 years of Soviet rule, Latvia had to contend with the presence of tens of thousands of disgruntled Soviet/Russian troops and a very large Russian-speaking minority. This minority was very dissatisfied with the ‘nationalizing’ policies of the Latvian government in the realms of citizenship, language, education and other policy fields. While Russia sought to link the troop withdrawal to changes in Latvian minority policy, the HCNM, together with other Western partners, succeeded in delinking the two, transforming a political (and potentially military) conflict into a legal dispute. For various reasons, the Russian government dragged its feet in withdrawing the troops — while most had left by August 1994, a small contingent remained in Latvia until 1998, when an early-warning radar station in the Western Latvian town of Skrunda was dismantled. In 1993 and early 1994, local newspapers were full of stories of Russian soldiers selling weapons and diesel on the black market and ignoring Latvian customs in exporting scrap metal and illegally felled timber. Many of these troops had joined forces with the local anti-independence movement during the latter years of perestroika. The Latvian political elite was impatient to negotiate the withdrawal of the troops, which were seen as a security threat and a hated symbol of the Soviet ‘occupation’. For his part, Yeltsin feared that a rapid withdrawal might lead to unrest, as there was