Multi-Jammer Environment (Barrage + Deceptive)

def _sigmoid(x: float | np.ndarray) -> float | np.ndarray:
    return 1.0 / (1.0 + np.exp(-np.clip(x, -500.0, 500.0)))

def rhs(t, y):
    d = np.empty(20)

    # --- target with mild evasion (coordinated turn) ---
    d[0] = y[3]
    d[1] = y[4]
    d[2] = y[5]
    d[3] = -omega_evade * y[4]
    d[4] = omega_evade * y[3]
    d[5] = 0.0

    # --- barrage jammer (3 states) ---
    J_power = y[6]
    J_duty = y[7]
    J_over_S = y[8]

    switch_val = _sigmoid(_K_SIG * np.sin(two_pi_over_T * t))

    d[6] = -J_power * inv_tau_j + J_max * switch_val
    d[7] = (switch_val - J_duty) * inv_tau_duty
    J_duty_safe = max(J_duty, 1e-10)
    d[8] = (J_power * J_duty_safe / S_signal - J_over_S) * inv_tau_js

    # --- deceptive false target (5 states: x, y, z, vx, vy) ---
    dec_x, dec_y, dec_z = y[9], y[10], y[11]
    dec_vx, dec_vy = y[12], y[13]

    d[9] = dec_vx
    d[10] = dec_vy
    d[11] = 0.0
    d[12] = -omega_false * dec_vy
    d[13] = omega_false * dec_vx

    # --- EKF covariance traces (4 states) ---
    for i in range(4):
        noise_contrib = noise_scale[i] * (1.0 + J_over_S * 0.1)
        d[14 + i] = -alpha_cov[i] * y[14 + i] + noise_contrib

    # --- adaptive thresholds (2 states) ---
    d[18] = (_sigmoid(_K_SIG * (J_over_S - JS_thresh)) - y[18]) * inv_tau_a1

    sep = np.sqrt(
        (dec_x - y[0]) ** 2
        + (dec_y - y[1]) ** 2
        + (dec_z - y[2]) ** 2
        + 1e-10
    )
    d[19] = (_sigmoid(_K_SIG * (sep / 100.0 - 0.5)) - y[19]) * inv_tau_a2

    return d