/**
 * @author @thkruz Theodore Kruczek
 * @license AGPL-3.0-or-later
 * @copyright (c) 2025 Kruczek Labs LLC
 *
 * Orbital Object ToolKit is free software: you can redistribute it and/or modify it under the
 * terms of the GNU Affero General Public License as published by the Free Software
 * Foundation, either version 3 of the License, or (at your option) any later version.
 *
 * Orbital Object ToolKit is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY;
 * without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
 * See the GNU Affero General Public License for more details.
 *
 * You should have received a copy of the GNU Affero General Public License along with
 * Orbital Object ToolKit. If not, see <http://www.gnu.org/licenses/>.
 */
import { EpochUTC, J2000, Matrix, Vector, Vector3D } from '../main.js';
import { Propagator } from '../propagator/Propagator.js';
import { RandomGaussianSource } from './../operations/RandomGaussianSource.js';
import { PropagatorPairs } from './PropagatorPairs.js';
/**
 * Observation data.
 */
export declare abstract class Observation {
    /** Observation epoch. */
    abstract get epoch(): EpochUTC;
    /** Inertial observer location. */
    abstract get site(): J2000;
    /** Observation noise matrix. */
    abstract get noise(): Matrix;
    /**
     * Return range-normalized cross line-of-sight residual for the observation
     * when compared against a nominal state propagator.
     * @param propagator Propagator to compare against.
     * @throws Not implemented.
     */
    clos(propagator: Propagator): number;
    /**
     * Return relative state residual for the observation when compared against
     * a nominal state propagator.
     * @param propagator Propagator to compare against.
     * @throws Not implemented.
     */
    ricDiff(propagator: Propagator): Vector3D;
    /**
     * Convert this observation to vector form.
     * @throws Not implemented.
     */
    toVector(): Vector;
    /**
     * Compute the state derivative matrix for this observation.
     * @param propPairs Propagator pairs to compare against.
     * @throws Not implemented.
     */
    jacobian(propPairs: PropagatorPairs): Matrix;
    /**
     * Compute the state residual matrix for this observation.
     * @param propagator Propagator to compare against.
     * @throws Not implemented.
     */
    residual(propagator: Propagator): Matrix;
    /**
     * Convert this observation's noise matrix into a covariance matrix.
     * @returns A matrix representing the noise covariance.
     */
    noiseCovariance(): Matrix;
    /**
     * Generates a noise sample from the noise covariance matrix.
     * @param sigma - The scaling factor for the noise covariance matrix.
     * @returns A matrix representing the noise sample.
     */
    noiseSample_(sigma: number): Matrix;
    /**
     * Randomly sample this observation in vector form within the
     * observation noise.
     * @param random Random number generator.
     * @param sigma Sigma value to scale the noise by.
     * @returns Sampled observation.
     */
    sampleVector(random: RandomGaussianSource, sigma: number): Vector;
    /**
     * Randomly sample this observation within the observation noise, scaled to
     * the provided sigma value.
     * @param random Random number generator.
     * @param sigma Sigma value to scale the noise by.
     * @throws Not implemented.
     */
    sample(random: RandomGaussianSource, sigma?: number): Observation;
}