To characterize atmospheric turbulence, the Doppler moments are estimated by weather radars. However, moment accuracy is highly sensitive to radar transmission parameters such as pulse repetition time (T_s) and number of pulses (N_p), which affect Doppler ambiguity and estimation variance. Traditional fixed-parameter radars face trade-offs between aliasing and measurement precision. This paper proposes an adaptive radar framework that dynamically adjusts T_s and N_p on a per-scan basis to improve Doppler moment estimation at a single resolution cell level. Inspired by the Fully Adaptive Radar (FAR) concept, the method also includes a novel multi-lag Doppler width estimation scheme. Results demonstrate enhanced estimation accuracy, enabling better responsiveness to localized and non-stationary weather conditions.

Conventional radar segmentation research has typically focused on learning category labels for different moving objects. Although fundamental differences between radar and optical sensors lead to differences in the reliability of predicting accurate and consistent category labels, a review of common radar perception tasks in automotive applications reveals that determining whether an object is moving or static is a prerequisite for most tasks. To fill this gap, this study proposes a neural network (NN)-based solution that can simultaneously segment static and moving objects from radar point clouds. Furthermore, since the measured radial velocity of static objects is correlated with the motion of the radar, this approach can also estimate the instantaneous 2-D velocity of the moving platform/vehicle (ego-motion). Notably, despite performing dual tasks, the proposed method employs very simple yet effective building blocks for feature extraction: multilayer perceptrons (MLPs) and recurrent NNs (RNNs). In addition to being the first of its kind in the literature, the proposed method also demonstrates the feasibility of extracting the information required for the dual tasks directly from unprocessed point clouds, without the need for cloud aggregation, Doppler compensation, motion compensation, or any other intermediate signal processing steps. To measure its performance, this study introduces a set of novel evaluation metrics and tests the proposed method using a challenging real-world radar dataset, RadarScenes. The results show that the proposed method not only performs well on the dual tasks but also has broad application potential in other radar perception tasks. More qualitative results can be viewed here: https://youtu.be/3ejS1chSvQ8?si=uGRugVA63BCyvNBV

An antenna array with dual-functionality - electromagnetic radiation and thermal cooling - is proposed. An iterative array design procedure is developed to improve cooling, mutual coupling, side lobe levels, and gain levels in dual-functional antenna arrays with adaptive beam steering. Heatsink-attached patch elements are combined with complementary split ring resonator (CSRR) structures in between the elements, resulting in a novel modular heatsink antenna array. Based on the proposed design, the beam scanning performances of four-element and eight-element linear arrays at 26 GHz are studied. A conventional shorted patch antenna array is used for benchmarking. Through thermal and electromagnetic simulations, it is demonstrated that the proposed antenna array decreases the maximal array temperature by more than 40°C as compared to the benchmark. Moreover, the new design resolves the pattern performance degradation problems in heatsink arrays, while approaching to the electromagnetic performance of the benchmarked array.

A novel over-the-air (OTA) measurement setup for simultaneous and near-real-time characterization and mapping of the phased array radiation patterns to the error-vector-magnitude (EVM) is introduced. A cost-effective software-defined radio (SDR) system, including a Pluto SDR for both transmission and reception, is employed. For setup demonstration, the performance of a 4 × 4 active phased array antenna (APAA) is studied at 26.5 GHz. Calibration of the transmitter results in an EVM of 0.5%, proving the accuracy of the measurement system. The over-the-air measured EVM of the APAA is 1.2%. The proposed setup and approach provide deep insights into how array radiation characteristics affect signal quality, advancing the evaluation and development of APAAs for next-generation wireless communication systems.

This article offers a wide perspective of the research topic of orthogonal time–frequency space (OTFS)-based integrated radar–communication systems. OTFS modulation is a recently proposed evolution of orthogonal frequency division multiplexing that promises better Doppler tolerance and therefore is a firm candidate for future communications in high-mobility scenarios. As radar sensing is often present in these scenarios (urban mobility, drones), OTFS is also a firm candidate for multifunctional systems capable of communications and radar sensing. In this article, we present the state of the art of OTFS for integrated sensing and communications (ISAC), focusing on radar receiver and multiple-input multiple-output (MIMO) waveform design, and from this overview, we identify a set of open research challenges that are used to identify opportunities for research in the topic. It is shown that OTFS-based ISAC is an emerging topic with promising first results and plenty of room for growth.

An overview of polarimetric sensing and its growing application in automotive radar systems is presented. While polarimetric techniques are extensively used in fields like weather monitoring and target imaging, their integration into automotive radar presents unique challenges, particularly in calibration and measurement accuracy across wide scanning angles. This paper reviews key polarimetric principles and their use in different applications, with a focus on current automotive radar implementations, and the calibration challenges posed by off-broadside measurements. Future research directions for improving polarimetric accuracy in dynamic automotive environments are also discussed.

The throughput performance of intelligently shaped and fixed analog elevation beam patterns in millimeter-wave (mm-wave) base stations with hybrid beamforming (HBF) is assessed for the first time. Distinct spatially heterogeneous user distributions (i.e., uniform, near-site, cell-edge, and weighted uniform and near-site) and propagation environments (i.e., line-of-sight (LoS) with multipath and non-line-of-sight (NLoS) with multipath) are considered. The cosecant-squared and flat-top shaped beam patterns are compared to the benchmark pencil beam pattern with a straightforward electrical downtilt. The LoS simulation results show that in case of unknown weight of user distribution scenarios, the cosecant-squared pattern is the most robust, with a gain of up to 16% in the average system throughput and up to 34% in the 90th percentile user throughout compared to the benchmark. If the near-site case has a greater probability of occurrence than the uniform user distribution (e.g., due to daily events and festivals), the flat-top pattern becomes preferable. In the NLoS scenario, the considered HBF architectures with elevation beam pattern shaping do not bring any performance disadvantages compared to the benchmark HBF.

A novel system design framework is proposed for hybrid beamforming receivers to reduce the power consumption withoutany loss in sensitivity or beam scanning performance. Only the amplitude taper that corresponds to the relative individual analog subarrays is applied in the analog beamforming domain, while the rest of the taper is applied using digital beamformingcoefficients. Based on a given array size, number of beams, and the desired sidelobe suppression level, the number of analog subarrays and the beamforming integrated circuit (BFIC) component characteristics are optimally selected. An improved BFIC module is recommended that has less analog pre-amplification and a smaller dynamic range of variable attenuator steps. For concept demonstration, a benchmark analog beamforming and hybrid beamforming SatCom architecture, without this improvement, are simulated using a joint signal and power consumption analysis. For a 32 × 32 element array with 2 simultaneous beams and 30 dB side lobe tapering, the analog benchmark and hybrid benchmark (with 64 subarrays) are simulated to have a power consumption of 50.1 W and 66.5 W, respectively, A similar hybrid beamforming architecture with modified BFIC modules is shown to have a total power consumption of 40.3 W, less than both benchmarks. Furthermore, a comprehensive analysis of the system is conducted to illustrate how power consumption is influenced by the chosen number of subarrays with respect to the targeted sidelobe suppression, array size, number of beams and number of ADC bits.

The problem of reconstructing 3D signatures of human activities for monitoring and classification is considered in this work. A method based on data fusion from distributed MIMO (multiple-input multiple-output) radar nodes is developed in order to generate 3D intensity maps and related voxel-wise velocity vectors. The proposed method was evaluated with a dataset collected using three 60 GHz radars and including 7 activities performed by 30 participants. The results show that both static postures and dynamic activities can be captured effectively: consecutive phases of activities/movements can be identified by combining spatial intensity and velocity vectors, and the participant can be localized in the area under test. Furthermore, initial promising classification results of 98.3% macro F1-score are demonstrated in a three-class problem using the proposed 3D intensity maps and velocity vectors as inputs to a Convolutional Neural Network classifier.

The feasibility of using hybrid additive manufacturing (AM) to produce low-cost, phased array antennas for SatCom applications is investigated in this work. A 4x2 planar array comprised of dielectric resonator antennas (DRAs) operating in the fundamental mode within the K-band SatCom downlink band (17.7-21.2 GHz) has been designed, fabricated and measured. The impact of print settings on the material properties is assessed and incorporated into the antenna design process. Manufactured prototypes of the single element and the planar array geometry are experimentally verified in terms of their scattering parame-ters and far-field radiation patterns. The potential of combining hybrid AM and DRA technologies for future mmWave phased array developments is highlighted by the presented results.

The effect of amplifier-related signal amplitude compression in orthogonal time-frequency space (OTFS) waveform for radar and communications systems is considered. A novel approach to OTFS waveform generation is proposed, where complementary sequences are used with the Zak transform to encode delay-Doppler symbols and form an OTFS time-domain signal with a constant envelope. The high peak-to-average power ratio (PAPR) of conventional OTFS can cause amplifier saturation, leading to spectral noise and performance degradation in both communication and radar systems due to amplitude clipping. This issue can be critical in dual-function radar and communication applications, where high power may be crucial in both use cases. The proposed waveform, namely, constant modulus OTFS (CM-OTFS), offers an alternative to standard OTFS when high-power or low-cost amplification is required. The sensing and communications performances of CM-OTFS are evaluated through numerical simulations and compared with pristine and amplifier-distorted OTFS waveforms. CM-OTFS demonstrates slightly degraded sensing performance and lower communication rate than pristine OTFS but outperforms amplifier-distorted OTFS signals. The performance of CM-OTFS is evaluated through radar and communication simulations, as well as radar measurements using the waveform-agile PARSAX radar.