MI-based optimal jamming waveform design

This study investigates the problem of low probability of intercept (LPI)-based distributed multiple-input multiple-output (MIMO) radar waveform design against barrage jamming in signal-dependent clutter and coloured noise. Given the priori knowledge of the extended target impulse response, signal-dependent clutter, barrage jamming signals and coloured noise, the LPI-based scheme for optimal radar waveform design is proposed to minimise the total power consumption of the MIMO radar system by optimising the transmitted waveforms of different transmitters with a predetermined mutual information (MI) constraint for target characterisation performance. Firstly, the MI between the received echoes from the target at each receiver and the target impulse response is derived as a practical metric to characterise the parameter estimation performance of a target. Then, the LPI-based distributed MIMO radar waveform design strategy is developed. The resulting radar waveform optimisation problem is convex and solved analytically, whose solutions represent the optimum power allocation for each transmitter in the MIMO radar system. With the aid of numerical simulations, it is illustrated that to minimise the total transmission power, the optimal waveform should match with the target, clutter, jamming and coloured noise. In addition, it is also demonstrated that the LPI performance of the MIMO radar system can be significantly improved by employing the proposed radar waveform design scheme.

This paper addresses the problem of adaptive sequential waveform design for system parameter estimation. This problem arises in several applications such as radar, sonar, or tomography. In the proposed technique, the transmit/input signal waveform is optimally determined at each step, based on the measurements in the previous steps. The waveform is determined to minimize the Bayesian Cramer-Rao bound (BCRB) for estimation of the unknown system parameter at each step. The algorithm is tested for spatial transmit waveform design in multiple-input multiple-output radar target angle estimation at very low signal-to-noise ratio. The simulations show that the proposed adaptive waveform design achieves significantly higher rate of performance improvement as a function of the pulse index, compared to identical signal transmission.

To improve the target recognition and classification performance of integrated radar and communications system in signal-dependent interference, we propose an innovative robust adaptive orthogonal frequency division multiplexing integrated radar and communications waveform design taking into account the clutter. We set the uncertainty class for clutter and other prior information to solve the problem of system performance degradation caused by inaccurate information in actual environments. Then, we formulate the optimization function to maximize the normalized weighted sum of mutual information and data information rate subject to the constraint of the total transmitted energy. To solve the optimization problem, we propose a maximum marginal allocation algorithm that transforms the original problem into a multi-stage energy distribution problem, and performs optimal energy distribution in each stage according to the optimization criteria. Moreover, by considering a more practical scenario of multiple downlink communication users, a joint scheme for channel allocation and waveform design is presented to ensure the fairness of multiple communication users. Simulation results show the effectiveness and feasibility of the designed waveform and channel allocation method.

With the development of high speed digital processor and solid state power electronics, more flexible waveforms become feasible to achieve by modern radar systems. In fact, the choice of waveforms has a significant impact on the performance of radar systems. In this paper, we review the conventional radar waveform design as well as explore the new generation of waveforms via different theoretical methods, including the most recent wavelet based waveforms. It is shown that the waveform design supports the radar advancement for more intelligent and divergent applications. In this endeavor, radar waveform design plays an even more important role in reaching specific purposes, in addition to range and speed detections, and further improves the performance and application scopes of radar systems.

Radar jamming waveform design is a vital part of radar jamming. Over seven to eight decades of evolution, the field has transitioned from noise signal design to coherent jamming signal design, resulting in a multitude of complex jamming styles capable of achieving deceptive jamming, suppressive jamming, and smart noise jamming, which combines both deception and suppression. For the first time, this article establishes a general formula for unifying jamming waveform design. Building upon this foundation, we systematically categorize jamming techniques, and provide an in-depth summary of the corresponding principles and conduct comparative analysis of their effectiveness against different targets. Finally, we look forward in terms of future research directions in jamming waveform design, including quantifiable jamming effect evaluation indicators, combined jamming styles, and intelligent jamming waveform generation methods to address the continuous advancement of radar technology and the complexity and variability of the electromagnetic environment. In order to fill the gap in the literature by summarizing the current state of the field and highlighting key challenges and opportunities, this review provides a comprehensive overview of radar jamming waveform design, categorizes and compares different jamming techniques, and identifies future research directions.

We consider waveform design for radar space time adaptive processing (STAP), accounting for the waveform dependence of the clutter correlation matrix. It was shown previously in [1], that the joint problem of receiver weight vector optimization and radar waveform design is an intractable optimization problem, and constrained alternating minimization was proposed. In this paper, we propose projected gradient minimization. This minimization algorithm affords a numerically stable, lower computational complexity solution than the previously proposed alternating minimization. However, as a trade-off it results in larger iteration counts to achieve similar error variances of the STAP filter. Step size rules and the optimal step size for descent are derived analytically and validated via numerical simulations.

Optimal radar waveform design for target detection has been addressed in prior research literature under various assumptions regarding noise and clutter. A common model of the radar scene in work of this kind is a linear time-invariant (LTI) operator with additive Gaussian noise that acts on the transmitted signal to produce the received signal. This model is intrinsically ill-suited to dynamic scenes or moving radar platforms because it cannot account for Doppler. This paper introduces scene models based on Hilbert-Schmidt class (HS) operators on the space of finite-energy signals. This category of models generalizes the LTI category in the sense that every LTI operator is also a HS operator, but the HS class includes operators that account for frequency shifts as well as time shifts and are thus suitable for modeling radar scenes involving Doppler. Every HS operator is uniquely expressible as a superposition of elementary time and frequency shift operators, thus providing a convenient interpretation of a scene in terms of these physically meaningful operations on the transmitted signal. Application of this perspective to waveform design for target detection in noise and to optimal receiver processing for a given waveform for target detection in clutter and noise are demonstrated.

In this paper, a novel radar waveform phase function design is presented that constructs a radar waveform that spectrally manuevers around in-band co-channel interference (CCI) from active communications users that are co-channel with the radar system. The design approach treats the CCI problem as the physical interpretable problem of optical refraction where the time-frequency (TF) signature of the radar waveform is made to be analogous to a light ray propagating from a start time and position (frequency) to an end time and position (frequency) and will naturally accelerate through the CCI as if the equivalent light ray accelerated in through different mediums (with an index of refraction related to CCI power spectral density (PSD)). Using the Euler-Lagrange equations, we design the radar phase function that is used to modulate a constant modulus (CM) waveform. The radar waveform design will generally result in a nonlinear-frequency modulated (NLFM) waveform that provides improved signal-to-interference-plus-noise-ratio (SINR) on a potential target in the presence of CCI leading to improved probability of detection performance. We provide theoretical analysis and simulation results for the proposed waveform design.

The problems of multiple-input multiple-output (MIMO) radar adaptive waveform design in additive white Gaussian noise channels and multitarget recognition based on sequential likelihood ratio test are jointly addressed in this paper. Two information-theoretic waveform design strategies, namely, the optimal waveform for maximizing the mutual information (MI) between the extended target impulse response and the target echoes and the optimal waveform for maximizing the Kullback-Leibler (KL) divergence (or relative entropy), are applied in the multitarget recognition application. For multitarget case, two adaptive waveform design methods for all possible targets based on the current knowledge of each hypothesis are proposed. Method 1 is the probability weighted waveform method. Method 2 is the probability weighted target signature method. The optimal waveform is transmitted and adaptively changed such that a decision is made based on the likelihood ratio after several illuminations. Numerical results demonstrate that the best waveform is the KL divergence-based optimal waveform using Method 1 as it has the lowest average illumination number and the highest correct decision rate for target recognition. By optimally designing and adaptively changing the transmitted waveform, the average number of illuminations required for multitarget recognition can be much reduced.

In this paper, a low probability of intercepting radar waveform design method is proposed. The time-frequency image of the designed radar waveform is agile and random. Its time-frequency image is more complex than a chirp. This paper first determines the number of sub-pulses in a single pulse. Then find random points on the time-frequency plane of unit time and unit bandwidth. Finally, the randomly generated multi-component LFM signal is searched, and the waveform that meets the constraints, such as peak sidelobe level and main lobe width, is selected. Simulation results show that the peak sidelobe level of the waveform designed in this paper can reach as low as −23.44 dB, which is lower than the traditional chirp signal (-13.86 dB). The price is that the waveforms generated in this paper have a certain main lobe broadening compared to the traditional LFM. The simulation and analysis results show that the waveform designed in this paper is an effective low probability of intercepting radar waveform.

With the continuous evolution of wireless communication systems in terms of architectures, operating frequency bands, and network structures, the communication environment has become increasingly complex and exhibits diversified characteristics. In communication system testing, electromagnetic environment simulation, and countermeasure scenario research, higher requirements have been put forward for the flexibility of jamming signals regarding waveform types, parameter configuration, and transmission modes. However, traditional communication jamming equipment generally suffers from large volume, fixed functionality, and limited waveform types, making it difficult to adapt to rapidly changing application requirements. To address the above issues, this paper designs and implements a configurable jamming waveform generation platform based on an SDR system, focusing on the digital generation methods of various typical jamming waveforms on embedded FPGA platforms. The system utilizes the Zynq-7020 SoC as the signal processing core, combined with the AD9361 integrated RF transceiver chip, to construct a highly integrated baseband processing and RF transmission platform. Parameterized generation and modulation of various jamming waveforms—including single-tone, multi-tone, sweeping-frequency, and broadband noise—are implemented in the Programmable Logic side, with waveform parameter configuration and system operation control completed through the Processing System. Experimental results demonstrate that under limited volume and power consumption conditions, the system can stably generate multiple jamming signal forms, and its RF output spectral characteristics remain consistent with theoretical analysis results, verifying the feasibility and effectiveness of the proposed jamming waveform FPGA implementation method and system architecture.

This paper focuses on the radar waveform design in a spectrally crowded environment. A spectral constraint is forced on the radar waveform to ensure spectral compatibility with the overlayed licensed electromagnetic radiators. The waveform design problem is formulated by maximizing the output signal-to-interference-plus-noise ratio (SINR) under the energy, similarity and spectral constraints. Inspired by the feasibility and high-quality solution properties of feasible point pursuit successive convex approximation (FPP-SCA), we develop an efficient al-gorithm framework based on FPP-SCA to solve the waveform design problem. Numerical results demonstrate the effectiveness of the proposed algorithm.

In order to assess the radiation immunity performance of the vehicles in the actual electromagnetic environment, the radiation immunity test method based on the actual electromagnetic environment is studied. The test methods are analyzed from the aspects of electromagnetic environment acquisition and playback, field strength calibration, vehicle state setting and performance evaluation methods. The vehicle adaptability tests to actual electromagnetic environment are also carried out in actual location and in the 10m semi-anechoic chamber. The test results show that the vehicle malfunctions in the actual location can be effectively reproduced when tested in the 10m semi-anechoic chamber and the feasibility of the actual electromagnetic environment radiation immunity test method is preliminarily verified, which is of great significance for the enterprises to comprehensively evaluate the electromagnetic compatibility performance of the vehicles.

Simple pulsed radar is limited in range sensitivity by the average radiation power and, in range resolution by the pulse length. The design of any radar always involves a compromise between the two constraints. Waveform design aims to seek an appropriate harmony that best suits the relevant application. The pulse compression theory has been introduced in order to get a high range resolution as well as a good detection probability. One of the basic types of pulse compression is binary phase coding which encodes the transmitted pulse with information that is compressed (decoded) in the receiver of the radar. The study of the peak sidelobe level (PSL) binary sequences occurs as a classical problem of signal design for digital communication and, in equivalent guise, in analytic number theory. It has also become a notorious problem of combinatorial optimization. For years mathematicians, engineers, physicists and chemists have sought a systematic way to construct long binary sequences with low PSL. In this Chapter, we describe pulse compression technique in radar waveform design. In order to make the presentation self-contained, we start by providing a short summary of waveform design and an introduction to principle behind pulse compression by compiling the basic tools required for analyzing and comparing different radar signals. After that, we talk about binary sequence, its desired properties and general types of methods for finding and generating such waveforms. We keep on by an overview and introducing the existing methods and search routine done. We conclude the chapter with a brief survey of the results exhibited yet for low autocorrelation binary sequences. We mention a table of complete results presented and also introduce a histogram to unscramble them visually and predict the future.

In this paper, the problem of adaptive waveform design for cognitive radar (CR) in signal-dependent interference, as well as additive channel noise is investigated. With constraints on waveform energy and bandwidth, a flexible waveform optimization method taking both detection and range resolution into account is proposed. Unlike existing optimal waveforms designed by a single design criterion, waveform designed by the proposed method can be updated according to the environment information fed back by receiver and radar performance demands simultaneously at each cycle of CR. Simulations are conducted to illustrate that CR with the proposed waveform performs better than traditional radar system with fixed waveform, and offers more practical and flexible.