Recent publications show the potential of using orthogonal frequency division multiplexing (OFDM) waveforms as radar signals. Since the range resolution is proportional to the RF bandwidth, the major obstacle that obstructs the practical use in automotive and other low cost radars is the requirement to sample the received signal at sampling rates that span the whole RF signal bandwidth requiring ADCs with sampling rates in the order of GHz. This paper presents a method to achieve the high range resolution induced by a large RF bandwidth but with a much lower baseband bandwidth, consequently requiring a much slower ADC while at the same time delivering a velocity profile for each subcarrier. Additionally, the processing scheme induces a range migration compensation, independent of the number of targets. This is achieved with barely increased computational effort. The scheme is verified with simulations and measurements at 77 GHz.

No abstract

Next-generation radar sensors require imaging capabilities with high angular resolution. As for a single sensor, the aperture, and thus the achievable resolution, is limited due to the constraints of the front end, radar networks consisting of multiple sensors are a possible solution. However, their incoherency usually makes joint angle estimation impossible. This article presents a network concept consisting of an orthogonal frequency-division multiplexing (OFDM) radar and repeater elements, which receive the reflections from targets and retransmit them back to the radar. Thereby, any frequency conversion from radio frequency to baseband and vice versa is omitted such that the signal remains coherent to the initial transmit signal. To distinguish the bistatic signal transmitted by the repeater from the monostatic one of the OFDM radar, the orthogonal subcarrier structure of OFDM waveforms is exploited by combining a sparse radar transmit signal with a low-frequency modulation in the repeater. This allows to evaluate the bistatic signals at the radar with standard multiple-input-multiple-output (MIMO)-OFDM signal processing, leading to separate range-Doppler images for each virtual channel. Finally, it is shown that this method offers a coherent angular estimation based on the extended aperture of the network. For this purpose, a method to establish phase coherency by a reconstruction of the modulation phase is presented. The network concept is proved with measurements at 77 GHz.

Multi-carrier waveforms such as orthogonal frequency-division multiplexing (OFDM) found their way into radar applications in the last few years. However, currently, typically only a fraction of the large baseband bandwidth required to obtain high resolution is available in practice due to hardware limitations. In this paper, we propose a frequency agile sparse OFDM radar processing which allows the transmission of consecutive bandwidth-reduced OFDM pulses on different carriers and thereby covering a much larger measurement bandwidth in a measurement frame. Through joint processing of multiple narrowband pulses and compressed sensing methods, high resolution and unambiguity in the joint range-velocity profile is obtained comparable to an equivalent wideband OFDM. It shows that a baseband bandwidth of 20 % of the full channel bandwidth is sufficient to reliably obtain the same result as for an equivalent wideband OFDM signal. The proposed processing scheme is validated using simulations and radar measurements at 77 GHz.

In many applications, the direction of arrival (DoA) information of the radar signal plays a decisive role in target localization. A multiple-input multiple-output (MIMO) radar allows to obtain the position of an object in space within one measurement frame. Recent research and publications verify the high potential of digital radar principles such as orthogonal frequency-division multiplexing (OFDM). In this letter, a MIMO-OFDM approach based on random frequency and time-division multiplexing is presented. It is enhanced by a multidimensional compressed sensing method which utilizes the information of multiple channels. The approach is validated and compared to other MIMO-OFDM approaches using measurements of an experimental radar at 72.5 GHz.