![]() Alaeekerahroodi, Mohammad ![]() ![]() ![]() in Proceedings of EuRAD 2020 (in press) We present the design of discrete-phase sequences considering simultaneously the peak sidelobe level (PSL) and avoiding reserved frequency bands which are occupied by narrowband interferers or ... [more ▼] We present the design of discrete-phase sequences considering simultaneously the peak sidelobe level (PSL) and avoiding reserved frequency bands which are occupied by narrowband interferers or communications. We use the coordinate descent framework and propose an algorithm to design discrete-phase sequences with spectral power suppressed in arbitrary bands and with low auto-correlation sidelobes in terms of PSL. Our proposed algorithm exploits fast Fourier transform and is, therefore, computationally efficient. The over-the-air experiments using implementation on software-defined radio show reasonable agreement with numerical simulations and feasibility for field-deployment [less ▲] Detailed reference viewed: 17 (5 UL)![]() Alaeekerahroodi, Mohammad ![]() ![]() in Information Theoretic Approach for Waveform Design in Coexisting MIMO Radar and MIMO Communications (2020, May 14) We investigate waveform design for coexistence between a multipleinput multiple-output (MIMO) radar and MIMO communications (MRMC), with a radar-centric criterion that leads to a minimal interference in ... [more ▼] We investigate waveform design for coexistence between a multipleinput multiple-output (MIMO) radar and MIMO communications (MRMC), with a radar-centric criterion that leads to a minimal interference in the communications system. The communications use the traditional mode of operation in Long Term Evolution (LTE)/Advanced (FDD), where we formulate the design problem based on information-theoretic criterion with the discrete phase constraint at the design stage. The optimization problem, is nonconvex, multi-objective and multi-variable, where we propose an efficient algorithm based on the coordinate descent (CD) framework to simultaneously improve radar target detection performance and the communications rate. The numerical results indicate the effectiveness of the proposed algorithm in designing discrete phase set of sequences, potentially binary. [less ▲] Detailed reference viewed: 23 (0 UL)![]() Sedighi, Saeid ![]() ![]() in Sedighi, Saeid; Mishra, Kumar Vijay; Shankar, Bhavani (Eds.) et al Localization Performance of 1-Bit Passive Radars in NB-IoT Applications (2019, December 14) Location-based services form an important use-case in emerging narrowband Internet-of-Things (NB-IoT) networks. Critical to this offering is an accurate estimation of the location without overlaying the ... [more ▼] Location-based services form an important use-case in emerging narrowband Internet-of-Things (NB-IoT) networks. Critical to this offering is an accurate estimation of the location without overlaying the network with additional active sensors. The massive number of devices, low power requirement, and low bandwidths restrict the sampling rates of NB-IoT receivers. In this paper, we propose a novel low-complexity approach for NB-IoT target delay estimation in cases where one-bit analog-to-digital-converters (ADCs) are employed to sample the received radar signal instead of high-resolution ADCs. This problem has potential applications in the design of inexpensive NB-IoT radar and sensing devices. We formulate the target estimation as a multivariate fractional optimization problem and solve it via Lasserre's semi-definite program relaxation. Numerical experiments suggest feasibility of the proposed approach yielding high localization accuracy with a very low number of 1-bit samples. [less ▲] Detailed reference viewed: 86 (12 UL)![]() Sedighi, Saeid ![]() ![]() in Sedighi, Saeid; Shankar, Bhavani; Mishra, Kumar Vijay (Eds.) et al Optimum Design for Sparse FDA-MIMO Automotive Radar (2019, November 03) Automotive radars usually employ multiple-input multiple-output (MIMO) antenna arrays to achieve high azimuthal resolution with fewer elements than a phased array. Despite this advantage, hardware costs ... [more ▼] Automotive radars usually employ multiple-input multiple-output (MIMO) antenna arrays to achieve high azimuthal resolution with fewer elements than a phased array. Despite this advantage, hardware costs and desired radar size limits the usage of more antennas in the array. Similar trade-off is encountered while attempting to achieve high range resolution which is limited by the signal bandwidth. However, nowadays given the demand for spectrum from communications services, wide bandwidth is not readily available. To address these issues, we propose a sparse variant of Frequency Diverse Array MIMO (FDA-MIMO) radar which enjoys the benefits of both FDA and MIMO techniques, including fewer elements, decoupling, and efficient joint estimation of target parameters. We then employ the Cram\'{e}r-Rao bound for angle and range estimation as a performance metric to design the optimal antenna placement and carrier frequency offsets for the transmit waveforms. Numerical experiments suggest that the performance of sparse FDA-MIMO radar is very close to the conventional FDA-MIMO despite 50\% reduction in the bandwidth and antenna elements. [less ▲] Detailed reference viewed: 80 (8 UL)![]() ; Shankar, Bhavani ![]() in IEEE Signal Processing Magazine (2019), 36(5), 100-114 Synergistic design of communications and radar systems with common spectral and hardware resources is heralding a new era of efficiently utilizing a limited radio-frequency (RF) spectrum. Such a joint ... [more ▼] Synergistic design of communications and radar systems with common spectral and hardware resources is heralding a new era of efficiently utilizing a limited radio-frequency (RF) spectrum. Such a joint radar communications (JRC) model has advantages of low cost, compact size, less power consumption, spectrum sharing, improved performance, and safety due to enhanced information sharing. Today, millimeter-wave (mmwave) communications have emerged as the preferred technology for short distance wireless links because they provide transmission bandwidth that is several gigahertz wide. This band is also promising for short-range radar applications, which benefit from the high-range resolution arising from large transmit signal bandwidths. Signal processing techniques are critical to the implementation of mm-wave JRC systems. Major challenges are joint waveform design and performance criteria that would optimally trade off between communications and radar functionalities. Novel multiple-input, multiple-output (MIMO) signal processing techniques are required because mm-wave JRC systems employ large antenna arrays. There are opportunities to exploit recent advances in cognition, compressed sensing, and machine learning to reduce required resources and dynamically allocate them with low overheads. This article provides a signal processing perspective of mm-wave JRC systems with an emphasis on waveform design. [less ▲] Detailed reference viewed: 96 (4 UL)![]() Alaee-Kerahroodi, Mohammad ![]() in 2019 20th International Radar Symposium (IRS) (2019) Detailed reference viewed: 72 (2 UL)![]() Alaee-Kerahroodi, Mohammad ![]() in 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) (2019) Detailed reference viewed: 68 (5 UL)![]() Gharanjik, Ahmad ![]() ![]() in 2018 IEEE Statistical Signal Processing Workshop (SSP) (2018) We present a method for estimating rainfall by opportunistic use of Ka-band satellite communication network. Our approach is based on the attenuation of the satellite link signal in the rain medium and ... [more ▼] We present a method for estimating rainfall by opportunistic use of Ka-band satellite communication network. Our approach is based on the attenuation of the satellite link signal in the rain medium and exploits the nearly linear relation between the rain rate and the specific attenuation at Ka-band frequencies. Although our experimental setup is not intended to achieve high resolutions as millimeter wavelength weather radars, it is instructive because of easy availability of millions of satellite ground terminals throughout the world. The received signal is obtained over a passive link. Therefore, traditional weather radar signal processing to derive parameters for rainfall estimation algorithms is not feasible here. We overcome this disadvantage by employing neural network learning algorithms to extract relevant information. Initial results reveal that rainfall accumulations obtained through our method are 85% closer to the in situ rain gauge estimates than the nearest C-band German weather service Deutscher Wetterdienst (DWD) radar. [less ▲] Detailed reference viewed: 98 (0 UL) |
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