Radar Transmitter Research Articles

Periodic-Filtering Method for Low-SNR Vibration Radar Signal

Radar is a non-contact, high-precision vibration measurement device and an important tool for bridge vibration monitoring. Vibration information needs to be extracted from the radar phase, but the radar phase information is sensitive to noise. Under low signal-to-noise ratio (SNR) data acquisition conditions, such as low radar transmission power or a long observation distance, differential phase jump errors occur and clutter estimation becomes difficult, which leads to inaccurate inversion of vibration deformation. Traditional low-pass filtering methods can filter out noise to improve SNR, but they require oversampling. The sampling rate needs to be several times higher than the Doppler bandwidth, which is several times higher than the vibration frequency. This puts high data acquisition requirements on radar systems and causes large data volumes. Therefore, this paper proposes a novel vibration signal filtering method called the periodic filtering method. The method uses the periodicity feature of vibration signals for filtering without oversampling. This paper derives the time-domain and frequency-domain expressions for the periodic filter and presents a deformation inversion process based on them. The process involves extracting the vibration frequency in the Doppler domain, suppressing noise through periodic filtering, estimating clutter using circle fitting on the data complex plane, and inverting final deformation with differential phase. The method is verified through simulation experiments, calibration experiments, and bridge vibration experiments. The results show that the new periodic filtering method can improve the SNR by five times, resolve differential phase jumps, and accurately estimate clutter, thus getting submillimeter-level vibration deformation at low SNR.

An Experimental Study of Radar-Centric Transmission for Integrated Sensing and Communications

This study proposes a dual-function radar and communication (DFRC) system that utilizes radar transmission parameters as modulation indexes to transmit data to the users while performing radar sensing as its primary function. The proposed technique exploits index modulation (IM) using the center frequency of radar chirps, their bandwidths, and polarization states as indexes to modulate the communication data within each radar chirp. By utilizing the combination of these indexes, the proposed DFRC system can reach up to 17 Mb/s throughput, while observing a robust radar performance. Through our experimental study, we also reveal the trade-off between the radar sensing performance and communication data rate, depending on the radar waveform parameters selected in the DFRC system. This study also demonstrates the implementation of the proposed DFRC system and presents its real-time over-the-air experimental measurements. Consequently, the simulation results are verified by real-time over-the-air experiments, where ARESTOR, a high-speed signal processing and experimental radar platform, has been employed.

Joint Radar-Communication Optimization of Distributed Airborne Radar for AOA Localization

Compared to the distributed ground-based radar (DGBR), the distributed airborne radar (DAR) has been widely applied due to its stronger anti-damage ability, more degrees of freedom, and better detection view of targets. However, unlike DGBR, the premise for the normal operation of DAR is to maintain stable wireless communication between unmanned aerial vehicles (UAVs). This requires each UAV to make reasonable use of its electromagnetic domain resources. That is, to maximize radar detection performance while ensuring communication performance constraints. However, current research in the field of radar resource allocation has not taken this into account, which greatly limits the practical application of optimization algorithms. Moreover, the current research tends to adopt centralized optimization algorithms. When the baseline of the UAV swarm is long, applying multi-relay methods directly results in heavy communications overhead and long-time delay. Based on the above background, this article aimed to develop a fully distributed algorithm for the joint optimization of radar detection performance and communication transmission performance. This study first took the measurement angle of arrival (AOA) as an example to provide a system model with communication constraints. This model considers the impact of factors such as the UAV location error, UAV communication coverage, and dynamic communication topology of the UAV on joint optimization. A formal representation of the joint optimization is presented. Then, we proposed a joint radar-communication optimization (JRCO) algorithm to fully utilize the electromagnetic domain resources of each UAV. Finally, numerical simulations verified the effectiveness of the proposed JRCO algorithm to traditional radar resource allocation methods.

Airborne Radar Staggered PRF Coherent Processing Method for Down-Looking Target Detection

Airborne radar plays a crucial role in detecting aerial targets, but its detection capability can be significantly affected by strong ground clutter when operating in down-looking mode. The range-Doppler (RD) results of ground clutter in airborne radar may overlap the range-Doppler results of the targets, causing target occlusion and rendering them undetectable. In addition to target detection, accurate extraction of target parameters is also of great importance. Due to the high-speed movement of the airborne platform, targets may exhibit range-Doppler ambiguity, necessitating the use of appropriate methods to resolve the range-Doppler ambiguity. Aiming at the problem of target occlusion by clutter with range-Doppler two-dimensional ambiguity during airborne radar down-looking target detection, this paper conducts a study on the detection of airborne radar down-looking targets based on orthogonal signals combined with pulse repetition frequency (PRF) staggered transmission. An optimization method is employed to design multiple sets of PRF values, aiming to reduce the radar blind zone. The range-Doppler two-dimensional ambiguity of targets is resolved using multiple sets of PRF, and coherent processing is performed on the corresponding echoes using the transmission intervals, maximizing the utilization of radar transmission energy. This approach enhances the signal-to-noise ratio (SNR) and improves the detection performance and parameter estimation accuracy, particularly for low SNR targets. The superiority of the proposed approach is demonstrated through simulation experiments.

Solid Angle Geometry-Based Modeling of Volume Scattering with Application in the Adaptive Decomposition of GF-3 Data of Sea Ice in Antarctica

Over the last two decades, spaceborne polarimetric synthetic aperture radar (PolSAR) has been widely used to penetrate sea ice surfaces to achieve fully polarimetric high-resolution imaging at all times of day and in a range of weather conditions. Model-based polarimetric decomposition is a powerful tool used to extract useful physical and geometric information about sea ice from the matrix datasets acquired by PolSAR. The volume scattering of sea ice is usually modeled as the incoherent average of scatterings of a large volume of oriented ellipsoid particles that are uniformly distributed in 3D space. This uniform spatial distribution is often approximated as a uniform orientation distribution (UOD), i.e., the particles are uniformly oriented in all directions. This is achieved in the existing literature by ensuring the canting angle φ and tilt angle τ of particles uniformly distributed in their respective ranges and introducing a factor cos⁡τ in the ensemble average. However, we find this implementation of UOD is not always effective, while a real UOD can be realized by distributing the solid angles of particles uniformly in 3D space. By deriving the total solid angle of the canting-tilt cell spanned by particles and combining the differential relationship between solid angle and Euler angles φ and τ, a complete expression of the joint probability density function pφ,τ that can always ensure the uniform orientation of particles of sea ice is realized. By ensemble integrating the coherency matrix of φ,τ-oriented particle with pφ,τ, a generalized modeling of the volume coherency matrix of 3D uniformly oriented spheroid particles is obtained, which covers factors such as radar observation geometry, particle shape, canting geometry, tilt geometry and transmission effect in a multiplicative way. The existing volume scattering models of sea ice constitute special cases. The performance of the model in the characterization of the volume behaviors was investigated via simulations on a volume of oblate and prolate particles with the differential reflectivity ZDR, polarimetric entropy H and scattering α angle as descriptors. Based on the model, several interesting orientation geometries were also studied, including the aligned orientation, complement tilt geometry and reflection symmetry, among which the complement tilt geometry is specifically highlighted. It involves three volume models that correspond to the horizontal tilt, vertical tilt and random tilt of particles within sea ice, respectively. To match the models to PolSAR data for adaptive decomposition, two selection strategies are provided. One is based on ZDR, and the other is based on the maximum power fitting. The scattering power that reduces the rank of coherency matrix by exactly one without violating the physical realizability condition is obtained to make full use of the polarimetric scattering information. Both the models and decomposition were finally validated on the Gaofen-3 PolSAR data of a young ice area in Prydz Bay, Antarctica. The adaptive decomposition result demonstrates not only the dominant vertical tilt preference of brine inclusions within sea ice, but also the subordinate random tilt preference and non-negligible horizontal tilt preference, which are consistent with the geometric selection mechanism that the c-axes of polycrystallines within sea ice would gradually align with depth. The experiment also indicates that, compared to the strategy based on ZDR, the maximum power fitting is preferable because it is entirely driven by the model and data and is independent of any empirical thresholds. Such soft thresholding enables this strategy to adaptively estimate the negative ZDR offset introduced by the transmission effect, which provides a novel inversion of the refractive index of sea ice based on polarimetric model-based decomposition.

Preparation of paraffin wax-modified floating aluminum powder and composite coating with infrared stealth and wave-transparent function

Low Infrared (IR) emissivity coatings in military aerospace need to meet both stealth and radar transmission. At present, there are few research on this aspect, therefore how to solve the compatibility problem of low infrared emissivity and high radar wave transmission rate of materials is an important direction for the development of infrared stealth materials. A multi-functional composite coating with low IR emissivity, dielectric loss, and antistatic properties was prepared using modified floating aluminum powder (Al@PW), short-cut carbon fiber, and ethylene propylene diene monomer (EPDM) as the binder. The coating's properties were investigated, highlighting the effect of PW. The results indicate that modifying floating Al powder with PW is an effective solution to the trade-off between low IR emissivity and high wave transparency. At a dosage of 11 g (about 12.5 wt% in Al@PW), the coating demonstrated the best overall performance, including the IR emissivity of 0.582, the surface resistivity of 9.5 MΩ/□, the dielectric constant of 5.15, the dielectric loss angle tangent of 0.052, the tensile strength of 11.75 MPa, and the elongation at break of 516.10%. The composite coating may be used as a multi-functional protective coating for airborne radomes.

Deep Learning-Based Link Configuration for Radar-Aided Multiuser mmWave Vehicle-to-Infrastructure Communication

Configuring millimeter wave links following a conventional beam training protocol, as the one proposed in the current cellular standard, introduces a large communication overhead, especially relevant in vehicular systems, where the channels are highly dynamic. In this paper, we propose the use of a passive radar array to sense automotive radar transmissions coming from multiple vehicles on the road, and a radar processing chain that provides information about a reduced set of candidate beams for the links between the road-infrastructure and each one of the vehicles. This prior information can be later leveraged by the beam training protocol to significantly reduce overhead. The radar processing chain estimates both the timing and chirp rates of the radar signals, isolates the individual signals by filtering out interfering radar chirps, and estimates the spatial covariance of each individual radar transmission. Then, a deep network is used to translate features of these radar spatial covariances into features of the communication spatial covariances, by learning the intricate mapping between radar and communication channels, in both line-of-sight and non-line-of-sight settings. The communication rates and outage probabilities of this approach are compared against exhaustive search and pure radar-aided beam training methods (without deep learning-based mapping), and evaluated on multi-user channels simulated by ray tracing. Results show that: (i) the proposed processing chain can reliably isolate the spatial covariances for individual radars, and (ii) the radar-to-communications translation strategy based on deep learning provides a significant improvement over pure radar-aided methods in both LOS and NLOS channels.

Revolutionizing IC Genset Operations with IIoT and AI: A Study on Fuel Savings and Predictive Maintenance

In a world increasingly aware of its carbon footprint, the quest for sustainable energy production and consumption has never been more urgent. A key player in this monumental endeavor is fuel conservation, which helps curb greenhouse gas emissions and preserve our planet’s finite resources. In the realm of the Industrial Internet of Things (IIoT) and artificial intelligence (AI) technologies, Caterpillar (CAT) generator set (genset) operations have been revolutionized, unlocking unprecedented fuel savings and reducing environmental harm. Envision a system that not only enhances fuel efficiency but also anticipates maintenance needs with state-of-the-art technology. This standalone IIoT platform crafted with Visual Basic.Net (VB.Net) and the KEPware Object linking and embedding for Process Control (OPC) server gathers, stores, and analyzes data from CAT gensets, painting a comprehensive picture of their inner workings. By leveraging the Modbus Remote Terminal Unit (RTU) protocol, the platform acquires vital parameters such as engine load, temperature, pressure, revolutions per minute (RPM), and fuel consumption measurements, from a radar transmitter. However, the magic does not stop there. Machine Learning.Net (ML.Net) empowers the platform with machine learning capabilities, scrutinizing the generator’s performance over time, identifying patterns and forecasting future behavior. Equipped with these insights, the platform fine tunes its operations, elevates fuel efficiency, and conducts predictive maintenance, minimizing downtime and amplifying overall efficiency. The evidence is compelling: IIoT and AI technologies have the power to yield substantial fuel savings and enhance performance through predictive maintenance. This research offers a tangible solution for industries eager to optimize operations and elevate efficiency by embracing IIoT and AI technologies in CAT genset operations. The future is greener and smarter, and it starts now.

Reliability modeling of modular k-out-of-n systems with functional dependency: A case study of radar transmitter systems

The k-out-of-n systems are among the most important redundancy structures in engineering practices, and their reliability assessment has been extensively studied in the past decades. However, components in a k-out-of-n structure are often subject to functional dependency (FDEP), in which component states are affected by other components’ states in the system. In this article, we study a new system structure, namely modular k-out-of-n system with FDEP. In such a system, the failure of some specific components will disable some components in the k-out-of-n structure. Bayesian network (BN) models are used to construct the structure function of modular k-out-of-n systems. The parameters encoded in the graphical structure of the modular k-out-of-n system are automatically generated by a customized algorithm. Furthermore, a dynamic BN (DBN) is developed to update the reliability of modular k-out-of-n system dynamically when observation data are collected from either component or system level. The Birnbaum importance measure of the different types of components in the modular k-out-of-n system is also evaluated by the DBN model via inserting evidence of the components’ states overtime. A real-world case of a radar transmitter system in the space launch site is studied to demonstrate the effectiveness of the proposed method.

The first polarimetric GNSS-Reflectometer instrument in space improves the SMAP mission’s sensitivity over densely vegetated areas

The Soil Moisture Active Passive (SMAP) mission has dramatically benefited our knowledge of the Earth’s surface processes. The SMAP mission was initially designed to provide complementary L-band measurements from a radiometer and a radar, producing geophysical measurements at a finer spatial resolution than the radiometer alone. Both instruments, sensitive to the geophysical parameters in the swath, provided independent measurements at different spatial resolutions. A few months after SMAP’s launch, the radar transmitter’s high-power amplifier suffered an anomaly, and the instrument could no longer return data. During recovery activities, the SMAP mission switched the radar receiver frequency facilitating the reception of Global Positioning System (GPS) signals scattered off the Earth’s surface, and enabling the radar to become the first spaceborne polarimetric Global Navigation Satellite System – Reflectometry (GNSS-R) instrument. With more than 7 years of continued measurements, SMAP GNSS-R data are the most extensive existing GNSS-R dataset and the only one providing GNSS-R polarimetric measurements. We demonstrate that the SMAP polarimetric GNSS-R reflectivity, derived from Stokes parameters mathematical formulation, can enhance the radiometer data over dense vegetation areas, recovering some of the original SMAP radar capability to contribute to the science products and pioneering the first polarimetric GNSS-R mission.

An Excavated PSO-SQP Mechanisms for an Effective Radar Transmission in MIMO-OFDM Communication Systems

An Excavated PSO-SQP Mechanisms for an Effective Radar Transmission in MIMO-OFDM Communication Systems

The Influence of the Internal Properties of River Ice on Ground Penetrating Radar Propagation

Ground penetrating radar (GPR) has proven to be a very effective method for examining ice thickness. However, two preconditions must be met for this approach to be useful; the round-trip travel time of electromagnetic (EM) waves and radar transmission speed in the ice must be known. These issues are problematic because many factors affect radar transmission speed in ice, including impurities, physical properties such as porosity and density, and temperature. Results show that if these factors are not taken into account and a signal velocity of 0.17 m/ns in pure ice is used to estimate thickness, overestimates will result. We carried out a series of GPR surveys using dual channel host 200 MHz shielded antennas at the Toudaoguai Hydrological Station on the Yellow River, China, and collected samples to analyze ice impurities and physical properties. The results show that the ice crystal types include frazil, granular, and column at the Toudaoguai Hydrologic Station section. Our analysis of ice gas bubble and sediment content showed that the gas bubble volume content is between 11.95 and 13.0% in the frazil ice and between 7.9% and 8.6% in granular and columnar ice. At the same time, the ice sediment content ranged between 0.11‰ and 0.57‰, and the average was 0.24‰ in granular and columnar ice, which was about one-tenth that of the suspended sediment concentration in water. Additionally, a combination of GPR data as well as ice impurities, porosity, density, and temperature enabled us to provide insights on the variability of radar transmission speed and the equivalent dielectric permittivity in river ice. Our extensive observations reveal that radar transmission speed falls between 0.141 m/ns and 0.164 m/ns and that the equivalent dielectric permittivity of river ice increases in concert with ice temperature.

A compact dual band T-shaped monopole antenna for WLAN and C-band application

The design of a compact monopole dual-band antenna suitable for dual-band applications is proposed in this research. The antenna consists of eight rectangular patches, each measuring 40 × 30 × 1.6 mm³. It is designed to operate in two frequency bands: 2.18–2.63 GHz and 7.10–7.91 GHz, with resonance frequencies at 2.4 GHz and 7.5 GHz, ensuring a return loss (S11) of less than 10 dB. The results demonstrate that the proposed antenna achieves a bandwidth of 450 MHz (2.18–2.63 GHz) and 810 MHz (7.10–7.91 GHz). This bandwidth coverage allows for the inclusion of the 2.4 GHz range required for WiMAX as well as the 7.5 GHz range suitable for short-range radar and wireless data transmission applications. The antenna is simulated using HFSS v13 software, providing an accurate and reliable analysis of its performance. The compact size of the antenna makes it suitable for integration into various wireless devices and systems, offering versatility and adaptability. Overall, the presented compact monopole dual-band antenna demonstrates its efficacy in achieving dual-band operation, covering essential frequency ranges for WiMAX, short-range radar, and wireless data transmission applications. Its compact design and wide bandwidth make it a valuable candidate for modern wireless communication systems.

A Plasma-Switch Impedance Tuner With Microsecond Reconfiguration

With many frequency bands previously allocated solely for radar now being reallocated for sharing, radar transmitters must be frequency-agile, able to quickly change operating frequency while maintaining detection range. This article details the design of a 2–4-GHz reconfigurable impedance tuner using 35-W plasma switches. The tuner consists of switched shunt capacitor and inductor branches loading a series microstrip line. For many RF matching applications, a reconfigurable impedance tuner must have a broad tuning bandwidth, real-time switching speeds, high power handling, low loss, and broad Smith chart coverage. The implementation of the tuner using semiconductor plasma switches illuminated by laser diodes is described. The tuner is demonstrated in measurements using a custom search algorithm, adjusting and optimizing the tuner settings to provide maximum output power in approximately <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$300~\mu \text{s}$ </tex-math></inline-formula> upon changes in operating frequency or antenna impedance. This tuner provides superior reconfiguration times over other high-power tuners in the literature. The tuner possesses losses as low as 0.77 dB and at least 30% Smith chart coverage over the entire tunable bandwidth. With a 26.7- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{s}$ </tex-math></inline-formula> switching speed, the impedance tuner is also demonstrated to handle 20 W of power at all frequencies and states with over 40 W of power for greater than half of the octave bandwidth and power handling measured as high as 70 W. The combination of fast reconfiguration and high power handling in an impedance tuner can enable cognitive radar systems to adapt to a congested and dynamic environment in real time.

CMOS Platform for Everyday Applications Using Submillimeter Electromagnetic Waves

CMOS (Complementary Metal Oxide Silicon) integrated circuits (ICs) technology is emerging as a means for realization of capable and affordable systems that operate at frequencies near 300GHz and higher. This is lowering a key barrier for utilizing the sub-millimeter electromagnetic waves in everyday applications. Despite the fact that the unity maximum available gain frequency, fmax of NMOS transistors (with connections to the tope metal layer) has peaked at 320 GHz, signal generation up to 1.33 THz, coherent detection up to 1.2 THz and incoherent detection up to 10 THz have been demonstrated using CMOS integrated circuits. Furthermore, highly integrated rotational spectroscopy transceivers operating at frequencies up to near 300 GHz, 300-GHz and 400-GHz concurrent transceiver pixels and arrays for high resolution radar imaging, and 300-GHz and 390-GHz transmitters, and 300-GHz receivers for high data-rate communication have been demonstrated in CMOS. The performances of these CMOS circuits are sufficient or close to being sufficient to support electronic smelling using rotational spectroscopy that can detect and quantify concentrations of a wide variety of gases; imaging that can enable operation in a wide range of visually impaired conditions; and high-bandwidth communication. Lastly, techniques for affordable packaging and testing sub-millimeter wave systems are suggested based on experimental demonstrations.

A compact triple bands C shaped multiband monopole antenna for WLAN and WiMAX application

Antennas play a crucial role in communication as they serve as both transmitters and receivers. They are capable of supporting numerous applications and demanding higher bandwidth among which monopole antennas have emerged as a superior alternative to traditional antennas. A novel coplanar waveguide (CPW)-fed triple-band monopole antenna is proposed for WLAN and WiMAX applications. The antenna features a compact and simple Cshaped strip structure, allowing for easy fabrication. The prototype exhibits triple operating bands covering the required bandwidths of 2.4/5.2/5.8 GHz WLAN and 3.5/5.5 GHz WiMAX standards. Good radiation performance and antenna gain are achieved across the three frequency ranges. Another compact monopole multiband antenna is designed, consisting of five rectangular patches forming a C-shaped structure. It operates at frequencies covering WiMAX, WLAN, short-range radar, and wireless data transmission applications. The antenna demonstrates significant bandwidth to accommodate the respective frequency ranges required for these applications. The antenna design is simulated using HFSS v13 software.

Bistatic noise radar: Demonstration of correlation noise suppression

AbstractIn this study, spatial separation of the radar transmitter and receiver units is considered, as a means of reducing the masking effect in noise radars. A bistatic radar system is constructed, with emphasis on a lightweight transmitter unit that can be mounted on a commercial Unmanned Aerial Vehicle (UAV). The system uses pseudo‐random noise, generated digitally at the receiver and transmitter units. Correlation losses, due to non‐linearities in the transmitter and receiver units, are measured to 0.1 dB. This study shows that by separating the transmitter and receiver unit the masking effect is significantly reduced, compared to a monostatic setup. This reduction is enough for the system to detect a slow flying UAV. Thus, bistatic separation should be considered as a practical tool to reduce the masking effect. By processing clutter with an extended CLEAN algorithm, the correlation noise floor is further suppressed.

Linear polarization on radar cross section measurement for tank miniature

The use of radar technology, especially for the interests of state defense and security, has become the focus of development launched by the government of Indonesia. Equipment and vehicles in the defense and security sector are the top priority to be detected using radar technology. When a radar transmitter transmits its signal towards a target, some part of the signal will bounce in all directions or scattering, including to the receiver and some will be absorbed by the radar target. The radar target is assumed to have a small size, with the aim of focusing more on the beamwidth of the radar transmitting antenna to the target. This research has a focus on measuring radar targets in the form of defense equipment in the form of tanks made in miniature which are smaller than their original forms. The selected antenna polarization uses linear polarization with vertical and horizontal types. Each polarization will be compared with the value of the radar cross section (RCS) in the combination of the same polarization and different polarization. The measurement results show that the largest RCS value is obtained at an angle of 200° by 13 with a combination of Horizontal-Horizontal polarization and the smallest RCS value is obtained at an angle of 50° by -4 with a combination of Horizontal-Vertical polarization. With the results of these measurements, it can be concluded that the measurement of RCS for defense and security equipment can be carried out by measuring the miniature of the defense and security equipment

Multi-carrier broadband signal generation based on a mutually dual-domain mode-locked optoelectronic oscillator

A novel dual-domain mode-locked optoelectronic oscillator (DDML-OEO) is proposed and demonstrated to generate multi-carrier broadband signal. The DDML-OEO is built up by mode-locking a conventional OEO at the time domain and Fourier domain mutually. The Fourier domain mode locking (FDML) is achieved by driving the laser with a period triangular waveform voltage, of which the frequency is synchronized with the round-trip time of the OEO loop. Meanwhile, an electrical signal synchronizing with the free spectrum range (FSR) of the OEO loop is injected to realize the time domain mode locking (TDML) process. Through combined mechanisms of the FDML and TDML, the multi-carrier broadband signal can be directly generated via the DDML-OEO. Thanks to the TDML, different multi-carrier bands of the signal are coherent and the phase noise of the generated broadband waveform is strongly suppressed compared with free-running FDML-OEO. With the proposed scheme, an ultra-low phase noise of −111.1 dBc/Hz at 10 kHz offset for the generated multi-broadband signal waveform is achieved when the cavity length is about 3000 m. The bands interval, the bandwidth and the central frequency tunability are all discussed, which have great potential usage in multi-channel radar transmitter.

Adaptable waveform design for radar and jammer for multi-target using game theoretic strategies

In the environment of electronic warfare, the countermeasure between radar and jammer has become a hot issue. Finding the solution to optimal waveforms between them is very great significance. Aiming at the problem of multi-target detection in clutter environment, the authors propose the waveform optimization method based on signal-to-interference-plus-noise ratio (SINR) criterion for radar and jammer, respectively. When radar is the dominant player, the maxmin strategy is used to establish the optimization model to optimize the radar transmission waveform. When jammer is the dominant player, the minmax strategy is used to establish the optimization model to optimize the jammer waveform. When dealing with random multi-target, the authors also propose an adaptive weight method to solve the problem of summation of weighted multiple targets. Then, an improved method combined with Jensen’s inequality for radar and jammer is proposed, respectively, which could improve the detection performance of the radar system and reduce the computational complexity of maximum SINR-based method. The simulation results show that the proposed maximum SINR-based methods could adaptively allocate the transmission energy to improve the performance of the radar. The energy allocation of radar and jammer is slightly different under maxmin strategy and minmax strategy. The proposed improved methods could output the higher SINR than the maximum SINR-based methods. Both of the proposed methods could improve the performance of radar detecting targets.