Massive MIMO Radar for Target Detection

Abstract

Since the seminal paper by Marzetta from 2010, the Massive MIMO paradigm in communication systems has changed from being a theoretical scaled-up version of MIMO, with an infinite number of antennas, to a practical technology. Its key concepts have been adopted in the 5G standard and base stations with 64 fully-digital transceivers have been commercially deployed. Motivated by these recent developments in communication systems, this paper considers a co-located MIMO radar with MT transmitting and MR receiving antennas and explores the potential benefits of having a large number of virtual spatial antenna channels N = MT MR. Particularly, we focus on the target detection problem and develop a robust Wald-type test that guarantees certain detection performance regardless of the unknown statistical characterization of the clutter disturbance. Closed-form expressions for the probabilities of false alarm and detection are derived for the asymptotic regime N → ∞. Numerical results are used to validate the asymptotic analysis in the finite system regime under different disturbance models. Our results imply that there always exists a sufficient number of antennas for which the performance requirements are satisfied, without any a priori knowledge of the clutter statistics. This is referred to as the Massive MIMO regime of the radar system.

Opportunistic Interference Alignment for Spectrum Sharing between Radar and Communication Systems

“…The sum-rate performance of communication system according to with different P (i.e., number of radars) is shown in Figure 6 , where . Since is assumed by the large number of radar assumption [ 42 ], radars could not affect any ISI to BSs because transmit signal of radars are in the null space of effective interference channel between radar and BSs. Thus, it is shown that sum-rate performance of proposed OIAR is not changed by the number of radars, P , unlike conventional NSP technique.…”

“…Moreover, the number of selected UEs is smaller than the number of BS antennas (i.e., ) to effectively mitigate intra-cell interference of each cell. Besides, the number of radar antennas is assumed to be larger than sum of the number of antennas of all BSs in the communication system (i.e., ), so that the radar systems reliably detect targets while does not induce any interference to communication systems [ 42 ]. Furthermore, a line-of-sight (LOS) between each radar and its target of interest is assumed.…”

Incoherent Integration Detection Method of Airborne Phased Array Radar in a Multipath Environment

“…where λ ′ � λ I ′ + λ Q ′ , v ′ ≥ 0. en, with the help of the derivation ideas in [31,32], we can obtain the detection probability of V ′ as follows:…”

Robust Reinforcement Learning-based Wald-type Detector for Massive MIMO Radar

“…To minimize the risk of model mismatch, a very weak statistical assumption on the disturbance is made here [5, A1]: A1 The disturbance is a realization of a discrete-time, circular, complex random process with a polynomial decay of its autocorrelation function. Note that this assumption is weak enough to include most practical disturbance models such as autoregressive (AR), autoregressive moving average (ARMA) or general correlated Compound-Gaussian model [5].…”

“…However, no statistical guarantees are given on the overall detection performance under a variable disturbance distribution. In our recent paper [4], we proposed a novel approach to combine a robust Wald-type test, derived for Massive MIMO (MMIMO) radar system in [5], with a RL-based procedure. The aim was to maximize the detection performance of the resulting algorithm in an unknown environment.…”