Multi-target cognitive tracking method based on concentrated type MIMO radar

Abstract

The invention belongs to the technical field of radar system multi-target tracking and discloses a multi-target cognitive tracking method based on a concentrated type MIMO radar under complex environment. The multi-target cognitive tracking method based on the concentrated type MIMO radar comprises the following steps: setting the state (please see the specification for the formula) of the qth target at the moment K and a probability density function of the state; setting a measurement matrix to obtain the conditional probability density of the measurement matrix; calculating a Bayes information matrix (please see the specification for the formula) to obtain the relation a recursive relation between BIMs at the moment K and the moment K+1, and on the premise that the transmitting power is given, calculating the BCRB of a tracking error of the qth target at the moment k+1; establishing a power distribution model and solving the power distribution model, and transmitting a beam with corresponding power to the qth target at the moment K+1 according to a solved result.

Description

technical field [0001] The invention belongs to the technical field of radar system multi-target tracking, in particular to a multi-target cognitive tracking method based on a centralized MIMO radar in complex environments. Background technique [0002] Multi-target tracking in complex environments is a technical problem to be solved urgently for radar detection systems. Through the multi-beam working mode, the single-base centralized MIMO radar can track multiple targets, that is, obtain the motion state of multiple targets and the estimation results of RCS (radar cross-sectional area) parameters. In this mode of operation, each beam independently tracks a different target. Compared with the traditional single beam tracking mode, this method can prolong the dwell time of the beam on each target, thereby improving the Doppler resolution of the radar. [0003] Theoretically, the greater the transmit power of each beam of the radar, the better the tracking performance of eac...

AI Technical Summary

Problems solved by technology

It is mainly used to solve the problem of poor tracking performance of existing radars when performing multi-target tracking

Although the existing methods have achieved the goal of saving transmission power and optimizing the tracking effect, the whole method is based on the following two assumptions: 1) The radar cross section (RCS) information of the target is assumed to be known a priori ; 2) In the whole processing process, it is implicitly assumed that the detection probability of each target at each moment is 1, and there is no ideal situation of false alarm

On the one hand, in actual tracking, the RCS of the target needs to be estimated in real time, and the radar system cannot obtain its prior information before measurement; on the other hand, under the second assumption (that is, the detection probability of each target at each time is 1, and there is no ideal situation of false alarms), at each moment, the radar system can only obtain one measurement point about the target within the relevant gate (such as the range gate) of each target

However, this ideal detection condition cannot be met in practice

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