Automotive radar interference problem between multiple radar sensors is investigated. Phase-coded frequency modulated continuous wave (PC-FMCW) radar structure with low sampling and processing power demands is introduced to blindly mitigate mutual interference. The interference resiliency of the proposed structure is evaluated and compared with the conventional frequency modulated continuous wave (FMCW) automotive radar. It is demonstrated that the proposed approach is more robust to both coherent and non-coherent interference types, allowing resilience to both external interference of radars but also the self-interference in the simultaneous multiple input multiple output (MIMO) transmission.

A novel receiver structure for the reception of linearly frequency modulated (LFM) chirps carrying additional narrowband (phase) modulation is proposed. A linear relation between the time delay and the beat frequency shift of the target response in stretch processing is exploited to estimate the target range via correlation of the received signal with the replica in a Fractional Fourier Transform (FrFT) domain. According to numerical simulations, the proposed FrFT receiver demonstrates improved performance and computational efficiency over the state-of-the-art solutions for the moderate-to-large bandwidth of the information-carrying modulation. The receiver was integrated into the waveform-agile radar polarimetric agile radar in S band (PARSAX) and its performance has also been verified experimentally.

The calibration of a collocated MIMO radar is addressed by means of independent calibration of transmit and receive arrays. The solutions for both arrays' elements gain and phase terms only and the full coupling matrix estimation are presented. The proposed solution significantly improves over the conventional calibration of the virtual array in terms of calibration accuracy and reduced measurements requirement, as demonstrated by numerical simulation and validated by calibration of a commercial automotive radar.

The sensing properties of the binary phase codes are investigated with their application to phase-coded (linearly) frequency modulated continuous waveform (PC-FMCW). It is shown that the ambiguity function of FMCW signal modulated with a binary phase code corresponds to sheared ambiguity function of the code itself. The range profiles of PC-FMCW with different code families are analysed and compared in terms of integrated sidelobe level (ISL).

A generic description for common multi-carrier radar receivers is proposed. Two multi-carrier waveforms - orthogonal frequency division multiplexing (OFDM) and orthogonal time-frequency spacing (OTFS) - which could be used for joint radar and communication (JRC) applications - are considered. Sensing performances of different waveform-receiver pairs are compared theoretically. It is shown that while qualitatively, both waveforms perform similarly under the same receiver, performance differences exist between them.

Smoothed phase-coded frequency modulated continuous waveform (SPC-FMCW), which is aimed to improve the coexistence of multiple radars operating within the same frequency bandwidth, is studied, and the receiving strategy with a low analog-to-digital converter sampling requirement is investigated. The Gaussian filter is applied to obtain smooth waveform phase transitions, and then, quadratic phase lag compensation is performed before waveform transmission to enhance decoding. The proposed waveform is examined in different domains, and its waveform properties are analyzed theoretically and demonstrated experimentally. Both simulation and experimental results show that the introduced waveform with the investigated processing steps helps combine all advantages of the FMCW waveform, including hardware simplicity and small operational bandwidth of the receiver, with the advantages of phase coding.

In this paper, we propose a method for continuous monitoring of vital signs-in particular, respiration frequency-with a commercial mm-wave radar. The nearly constant frequency (NCF) model is adopted to represent chest displacement due to respiration and simulate radar response. Based on this model, an extended Kalman filter (EKF) based estimator is developed to track the breathing frequency of a person. The impact of dynamic model parameters is investigated in numerical simulation. The possibility to track breathing frequency with the proposed method is demonstrated by experimental data processing.

This paper presents an analysis of a new method of automotive radar self-calibration which uses targets of opportunity. While conventional offline calibration of a phased array antenna requires accurate knowledge of the positions of calibration targets relative to the radar, such information is not available in a dynamic scenario. To compensate for this, we have developed an estimation procedure based on an extended Kalman filter (EKF) to address the challenge of simultaneous localisation, mapping and calibration. The proposed technique makes it possible to compensate for moderate errors of amplitude and phase in the phased array response with just a few measured frames. A significant reduction in the sidelobe rejection of the array response, plus the ability to correct for angular steering errors, are demonstrated via numerical simulations and real data processing.

In this paper, the problem of on-the-fly estimation of the radar state (self-diagnostics) is considered. We propose to use repetitive objects of the road infrastructure, such as lampposts, for continuous diagnostics of the radar state. The selected approach allows accounting for the external factors, such as water layer or dirt on the bumper, which can significantly affect radar performance, but cannot be retrieved with the internal calibration. The statistical model for RCS of repetitive targets is considered, and the estimator of the actual radar gain from the received data is derived. It is demonstrated that observing a few tens of targets is sufficient to provide a reasonable estimation of the radar performance within the operational mode.