Recent Developments in Radar Waveforms (in English)

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.

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.

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.

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.

The key abilities of the cognitive radar system include learning new knowledge about its surroundings, critical decision-making, and adaptation to a constantly changing environment. Among others, cognitive radar aims to achieve optimal radar resource management and maximize target detection performance. Radar systems often have to operate in strongly interfered environments. This work investigates the novel research direction of cognitive radar system design based on artificial intelligence (AI) cognitive architectures. Namely, the integration of a coherent radar model with Soar cognitive architecture has been developed. This work describes in detail the sensorimotor subsystem, which represents radar signal processing algorithms and waveform design. The AI subsystem comprising of the long-term and short-term memories of the Soar architecture was also characterized. Cognitive memories are designed to represent radar environment state and solve signal-to-noise-ratio (SNR) maximization problem. Using computer simulations it has been shown that the proposed system improved target detection performance in comparison to traditional radar system.

The Pocket Radar Guide is a concise collection of key radar facts and important radar data that provides you with necessary radar information when you are away from your office or references. It includes statements and comments on radar design, operation, and performance; equations describing the characteristics and performance of radar systems and their components; and tables with data on radar characteristics and key performance issues. It is intended to supplement other radar information sources by providing a pocket companion to refresh memory and provide details whenever you need them such as in meetings, while traveling, or in the field.

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.

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In order to improve the estimation performance of radar system, previous studies on radar waveform design mostly focused on maximizing the mutual information between the target and the echo to design the transmitted waveform. However, these studies neglect the existence of jammer in the actual electromagnetic environment, so this paper introduces a jammer to design the corresponding jamming waveforms according to whether there are signal-related clutter or not, which weakens the estimation performance of radar system. Simulation results show that the energy allocation strategies of the two jamming waveforms are different.

The performance of modern radar systems mostly depends on the radiated waveforms, whose design is the basis of the entire system design. Today’s coherent, solid-state radars (either of the phased array type or of the single-radiator type as air traffic control or marine radars) transmit a set of deterministic signals with relatively large duty cycles, an order of 10%, calling for pulse compression to get the required range resolution. Often, power budget calls for different pulse lengths (e.g., short, medium, and long waveforms with a rectangular envelope) to cover the whole radar range. The first part of the chapter includes the topic of mitigating the effect of unwanted side lobes, inherent to every pulse compression, which is achieved both by a careful and optimal design of the waveform and by a (possibly mismatched) suitable processing. The second part of the chapter deals with the novel noise radar technology, not yet used in commercial radar sets but promising: (1) to prevent radar interception and exploitation by an enemy part and (2) to limit the mutual interferences of nearby radars, as in the marine environment. In this case, the design includes a tailoring of a set of pseudo-random waveforms, generally by recursive processing, to comply with the system requirements.

Radar performance is strongly dependent on the transmitted waveform and its parameters which must be adapted to the surrounding environment, radar mission, goal, and task. Waveform diversity is a relatively new paradigm involving a continuous variation and adaptation of the transmitted signal to dynamically optimize the radar performance and fulfill the more and more stressing requirements. In this context, cognitive radar waveform design in spectrally dense environments is a very challenging and topical problem. This paper deals with the synthesis of signals optimizing radar capabilities while satisfying spectral compatibility constraints. Specifically, the design of radar waveforms, sharing appealing features and ensuring spectral coexistence with other Radio Frequency (RF) systems, is introduced and discussed according to a rigorous framework.

This paper presents a technique for assessing the performance of continuous wave Doppler radar systems for physiological sensing. The technique includes an artificial target for testing physiological sensing radar systems with motion analogous to human heart movement and software algorithms leveraging the capabilities of this target to simply test radar system performance. The mechanical target provides simple to complex patterns of motion that are stable and repeatable. Details of radar system performance can be assessed and the effects of configuration changes that might not appear with a human target can be observed when using this mechanical target.

The problem of adaptive orthogonal frequency division multiplexing (OFDM) waveform design in the case of stochastic extended targets in the presence of strong and nonstationary interferences is an essential part of a cognitive radar system. In this article, a new approach is developed based on maximizing the mutual information between the random target impulse response and the received echoes with respect to the transmitted waveform. We use the advantage of OFDM signals and present an adaptive structure to match the complex weights of OFDM signal with the radar scene for making complete use of the transmission power. The interference reflections are utilized rather than eliminating them to design the weights of the transmitted OFDM signal. The optimization algorithm for designing transmitted signals is based on adaptive learning whose essential information is obtained by a feedback between receiver and transmitter. This feedback includes essential target and interference characteristics which extracted from the reflected echoes. Based on changes in interference features, the weights of the transmitted OFDM signal on each subcarrier are designed and transmitted in the next coherent processing interval. Experimental results reveal that the proposed approach achieves a higher rate of performance compared to nonadaptive waveform design approaches.

The design of waveforms play an important role in the performance of radar systems. Multicarrier complementary phase-coded signal has been a field of interest for many researchers due to its prominent properties. This paper aims to reduce the Peak-to-Mean Envelope Power Ratio (PMEPR) of a Multicarrier Complementary Phase-Coded (MCPC) signal consisting of P subcarriers which are phase modulated by P phase sequences. The carriers are equally separated in terms of frequency. The carrier separation is equal to the reciprocal of t <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> , which is equal to the span of each phase element, forming Orthogonal Frequency Division Multiplexing (OFDM). In this paper we propose a new approach to generate MCPC signal using Complementary Block Coding (CBC) method which has lower value of PMEPR in comparison with the conventional method.

We present a novel approach to the problem of dual-functional radar and communication (DFRC) waveform design with adjustable peak-to-average power ratio (PAPR), while minimizing the multi-user communication interference and maintaining a similarity constraint towards a radar chirp signal. The approach is applicable to generic radar chirp signals and for different constellation sizes. We formulate the waveform design problem as a non convex optimization problem. As a solution, we adopt the alternating direction method of multipliers (ADMM), hence iterating towards a stable waveform for both radar and communication purposes. Additionally, we prove convergence of the proposed method and analyze its computational complexity. Moreover, we offer an extended version of the method to cope with imperfect channel state information (CSI). Finally, we demonstrate its superior performance through simulations, in comparison to state-of-the-art radar-communication waveform designs.