Method for detecting targets using space-time adaptive processing and shared knowledge of the environment

• US 8,138,963 B1
• Filed: 09/10/2010
• Issued: 03/20/2012
• Est. Priority Date: 09/10/2010
• Status: Active Grant

• Current Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Original Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Inventors: Pun, Man-On, Sahinoglu, Zafer, Wang, Pu
• Primary Examiner(s): Tarcza, Thomas
• Assistant Examiner(s): Bythrow, Peter
• Application Number:
  US12/879,288
• Publication Number:
  US 20120062409A1
• Time in Patent Office: 557 Days
• Field of Search: 342/27, 342/104, 342/118, 342/147, 342/159, 342/175
• US Class Current: 342/27
• CPC Class Codes: G01S 13/04 Systems determining presence of a target based on relative movement of target G01S13/56
• CPC Class Codes: G01S 7/292 Extracting wanted echo-signals

Abstract

A method detects a target in a radar signal using space-time adaptive processing. A test statistic is

$T=\frac{\underset{\alpha }{\max }\underset{\lambda }{\max }\underset{R}{\int }{f}_1\left(x_0,x_1,\dots ,x_K❘\alpha ,\lambda ,R\right)p\left(R\right)dR}{\underset{\lambda }{\max }\underset{R}{\int }{f}_0\left(x_0,x_1,\dots ,x_K❘\lambda ,R\right)p\left(R\right)dR},$
where x₀ is a test signal, x_k are K training signals, α is an unknown amplitude of a target signal within the test signal, λ is a scaling factor, R is a covariance matrix of the training signals, and a function max returns a maximum values. The test statistic is compared to a threshold to determine whether the target is present, or not.

Claims

1. A method for detecting a target in a radar signal using space-time adaptive processing, comprising the steps:

using an electronic processor for determining a test statistic

2. The method of claim 1, wherein a hypothesis testing problem is used as follows

H₀:

x₀=d₀, x_k=d_k, k=1, . . . , K,

H₁;

x₀=aα

s+d₀, x_kd_k, k=1, . . . , K,

where a hypothesis H₀ is that the target is not present in the test signal, a hypothesis H₁ is that the target is present in the test signal, and d₀ and d_k are noise terms for covariance matrices of the test signal and training signals, respectively.

3. The method of claim 1, wherein the covariance matrix R is random and has a probability density function p(R), which is a function of a covariance matrix prior probability matrix R.

4. The method of claim 1, further comprising:

replacing the unknown amplitude α

by a maximum likelihood estimate of the amplitude α

.